The developments in the molecular biosciences have made possible a shift to combined molecular and system-level approaches to biological research under the name of Systems Biology. It integrates many types of molecular knowledge, which can best be achieved by the synergistic use of models and experimental data. Many different types of modeling approaches are useful depending on the amount and quality of the molecular data available and the purpose of the model. Analysis of such models and the structure of molecular networks have led to the discovery of principles of cell functioning overarching single species. Two main approaches of systems biology can be distinguished. Top-down systems biology is a method to characterize cells using system-wide data originating from the Omics in combination with modeling. Those models are often phenomenological but serve to discover new insights into the molecular network under study. Bottom-up systems biology does not start with data but with a detailed model of a molecular network on the basis of its molecular properties. In this approach, molecular networks can be quantitatively studied leading to predictive models that can be applied in drug design and optimization of product formation in bioengineering. In this chapter we introduce analysis of molecular network by use of models, the two approaches to systems biology, and we shall discuss a number of examples of recent successes in systems biology.

F.C. Boogerd , F.J. Bruggeman (Frank) , J.H.S. Hofmeyr , H.V. Westerhoff (Hans)
Multiscale Dynamics

Bruggeman, F.J, Hornberg, J.J, Boogerd, F.C, & Westerhoff, H.V. (2007). Introduction to systems biology. In F.C Boogerd, F.J Bruggeman, J.H.S Hofmeyr, & H.V Westerhoff (Eds.), Systems Biology: Philosophical Foundations (pp. 1–360). Elsevier.