Principal component analysis for bacterial proteomic analysis

Data-mining techniques are important for understanding biological phenotypes with large-scale datasets derived from comprehensive analysis such as shotgun proteomics. We attempted to illustrate differences of proteomic profiles among growth phase and cellular fractionation in Bacillus cereus by principal component analysis (PCA). In total, 10 proteins were picked up with significance biological phenotypes by PCA analysis. These results suggested that the PCA is useful tool for understanding proteomic analysis.