Understanding the functional aspects of cells as autonomous nonequilibrium processes requires knowing more than just the molecular players and their partner interactions. Another view is a "modular cell biology" perspective as proposed by Hopfield et al. (Nature, 402, 1999). In this talk I will illustrate how rules of organization of oscillators in regulatory biochemical networks emerge from measurements at the organismal level; that is, viewing the 'forest rather than the trees'. This is made possible, in part, with our development of a large data set microscopy and image analysis capability for measurement of large numbers of single cells of the organism Caulobacter crecentus. We are now able to elucidate fundamental insights about cell growth with high statistical precision. Our statistical mechanical generalization of an autocatalytic cycle, based on the deterministic derived in a deterministic ODE form by Hinshelwood, yields nontrivial predictions of temperature-dependence of the growth and division time distributions, a scaling relation of the distributions and a measure of the nonequilibriumness of cell growth. Extension of the approach to cell contour analysis and continuum modeling of cell shape during growth will be discussed. The idea of information flow by way of pulsed perturbation and response function measurements will also be presented.