The ultimate goal of systems biology is to generate mathematical models to comprehensively describe the dynamics of a biological system. Among all biochemical and informational systems that operate in cells, metabolism is unique because the composition and topology of the network of metabolic reactions is almost completely known. What is currently poorly understood, is how this system operates, how it is controlled and how it adapts to changing conditions of supply and demand. Most current models of metabolism and of biological processes in general are limited by the incompleteness and the restricted diversity of the data they are based on. In this project I propose to generate, for the first time, quantitative data sets of all metabolic proteins and their regulatory phosphorylation sites in the model organism yeast Saccharomyces cerevisiae, under a defined set of conditions. Such a comprehensive proteomic analysis will be achieved by means of a novel targeted proteomics approach, pioneered in the host group and which I preliminarily developed in the first months of my work. In the context of a well-established collaboration with metabolomics and computational systems biology groups at ETH Zurich, the generated proteomic and phosphoproteomics data on metabolic enzymes will be coupled to quantitative data of the associated mRNA transcripts, metabolites and metabolic fluxes. Integration of these different quantitative data types will be done with a genome-scale mathematical model of the whole yeast metabolism. The data generated will be unprecedented and the research will set us on a path towards the understanding of the control structure of S. cerevisiae metabolism and the identification of key regulation sites that actively control metabolic processes, advancing both the science of systems biology as well as our understanding of a universal biological system.