Ant Colony Optimization for Biomarker Identification from MALDI-TOF Mass Spectra

We present a novel method that combines ant colony optimization with support vector machines (ACO-SVM) to select candidate biomarkers from MALDI-TOF serum profiles of hepatocellular carcinoma (HCC) patients and matched controls. The method identified relevant mass points that achieve high sensitivity and specificity in distinguishing HCC patients from healthy individuals. The results indicate that the MALDI-TOF technology could provide the means to discover novel biomarkers for HCC