Red blood cell has many functions including oxygen and carbon dioxide transports, generation of metabolic energy, reducing agents, 2,3-bisphosphoglycerate. So the metabolic networks include the glycolysis, the pentose phosphate pathway, the 2,3-diphosphoglycerate shunt, and the pathway of nucleotide metabolism. In this thesis, three types of metabolic pathway models have been integrated to analyze the metabolism in the red blood cells. These are stoichiometric model for pathway analysis, flux balance analysis for metabolic flux analysis, and mathematical model for dynamic simulation.
When these techniques are applied to larger systems, some attentions are necessary. First, when optimal conversion yield is obtained from the elementary flux mode, it is noticed that some metabolites are used as intermediate metabolite or energy. If these metabolites are included in the system, it is very hard to judge the usage of these metabolites.
Second, when there exists exactly the same overall reaction for different pathways, it is noticed that optimal flux distribution is made from linear combination of these pathways. In order to have biological meaning, it should be considered together with some other aspects, such as dynamic behavior.
The three analysis techniques are the basis of metabolic engineering, which is the targeted improvement of cellular properties through modification of specific bioreactions (or introduction of new ones) with the use of rDNA technology. So methodologies used in this thesis can be useful for the analysis of complex metabolic network.