One of the most challenging problems in modern biology is to address at the experimental level the analysis of the dynamics of proteome variations in composition and structure in order to decipher the fundamental mechanisms of gene expression and regulation in normal and pathological conditions. Using U-[12C]-glucose as the sole source of carbon to grow prototrophic cells, we developed a Simple Light Isotope Metabolic (SLIM) labeling strategy highly effective to analyze with an unprecedented depth complex proteomes in bottom-up and top-down experiments. We want now to elaborate an automatic workflow processing of MS bottom-up raw data for quantitative proteomics. This requires robust statistical analysis of the SLIM-labeling based quantitative proteomics procedures. We want to apply the SLIM-labeling strategy to analyze the quantitative variations of proteoforms in top-down experiments, addressing the complexity of proteome from multi-cellular organisms and higher eukaryote cells.