Two stage optimization of biochemical pathways using parallel runs of global stochastic optimization methods

A disadvantage of global stochastic optimization methods is the stochastic convergence of the best value of the objective function to the global optimum. In spite those methods are widely used optimizing kinetic models of biochemical pathways. Moreover, the growing number of adjustable parameters in the model leads to combinatorial explosion of combinations of adjustable parameters if the best combination per number of adjustable parameters in the combination has to be found.