Computation procedure used in this study. In each round of 10 fold cross-validation, the whole dataset was randomly separated into training set and test set. Features that significantly differentiate the control class from the disease class are selected using training set only. Then test sets are classified by decision tree and ensembles using these features. Mass spec: mass spectrometry.