Systems biology provides new approaches for in silico metabolic engineering and drug development through the application of analysis, simulation and optimization methods for metabolic models. In silico modeling of cellular metabolism is divided between genome-scale stoichiometric models and small-scale kinetic models. While the former are analyzed using optimal assumptions predicting intracellular microbial fluxes and growth rates, the later are used for dynamic behaviour simulations. However, there is currently a separation between these two modeling approaches. In this talk, I will discuss my work related to the challenges to build novel computational approaches for complex large metabolic networks of biological systems and to fill the gap between kinetic and genome-scale stoichiometric models.