Parameter estimation for biochemical pathways by resolving inconsistent experimental data
In this study, a parameter estimation method has been developed for models of biomedical pathways. The inconsistency among experimental data that may come from different sources is reduced. The resulting parameters define a well-behaved mathematical model in the steady state. Based on experimental data collected separately from individual sub steps of a pathway, this approach achieves overall optimization in two steps: flux optimization and individual parameter optimization. The method is useful for identifying an initial state in modeling the dynamics of a biochemical pathway. The method has been effective as applied to a model of glycolysis.