Cancer cells have been shown to undergo a metabolic reprogramming, known as the Warburg effect, which results in enhanced glycolytic fluxes and down- regulated oxidative phosphorylation even in the presence of abundant oxygen. Experiments show that disruption of expression of enzymes that contribute to the enhancement of this glycolytic flux stimulates oxidative phosphorylation and leads to a decrease in tumor cell proliferation. Such observations have originated much interest in the study of tumor cell metabolism with the purpose of investigating possible targets for the development of new cancer therapies. Nevertheless, to date, the mechanistic details of this metabolic reprogramming, and in particular the physiological conditions that lead to the activation of this metabolic switch, have not been well characterized. Metabolic modeling has proven to be a valuable tool for the investigation of cellular physiology in metabolic engineering studies. Recently Hatzimanikatis and coworkers have developed a new framework called Flux Directionality Profile Analysis (FDPA) that aims to enumerate, characterize and rank all thermodynamically feasible intracellular flux states based on a pre-selected set of metabolic objectives. We apply the proposed methodology on a model of central carbon metabolism of mammalian cells in order to characterize the cellular physiology in terms of intracellular fluxes that are associated with the Warburg phenotype.