"The goal of Systems Biology is to provide a quantitative and predictive description of a living system to the extent that it can be fully simulated in a computer. We have undertaken such Endeavour using as a model the small bacterium, M. pneumoniae. use Mycoplasma pneumoniae, a human pathogenic bacterium causing atypical pneumonia as model system for our study. Containing a reduced genome with only 690 ORFs, this bacterium is an ideal organism for exhaustive quantitative and systems-wide studies, avoiding technical limitations due to exceeding sample complexity, constrained by limitations in dynamic range and resolution of current generation mass spectrometers. Available data on the transcriptome, on protein complexes, as well as on metabolic pathways facilitate the integration of the data generated for this study into an organism-wide context. Additionally, M. pneumoniae represents a relevant organism to study stochastic noise in living systems. The cells are significantly smaller than other bacteria, such as Eschericha coli (0.05 mm3 and 1 mm3, respectively) resulting in principle in an increased susceptibility to abundance fluctuations of cellular molecules. Our analysis shows that even apparently simpler organisms have a large hidden layer of complexity and that for every question we have answered we have got two new ones. We are still far away to be get a full understanding of a cell."