| 초록 |
The interpretation and prediction of metabolic flux distributions require mathematical modeling and computer simulation, and there exists a long history of quantitative metabolic modeling (Bailey, J.E., 1998). To deal with the lack of kinetic information, an alternative approach has been used to study feasible and optimal metabolic flux destributions: flux balance analysis (FBA). FBA provides a solution space that contains all possible steady-state distributions satisfing the applied constraints. Subject to the imposed constraints, optimal metabolic flux distributions can be determined from the set of all allowable flux distributions using linear programming (LP). To identify an optimal solution, it is necessary to establish an objective function. A number of different objective functions have been used for metabolic analysis. These include the following: 1) maximize ATP production, 2) minimize nutrient uptake, 3) minimize redox production, 4) maximize metabolite production, 5) maximize biomass and metabolite production (Edward et al., 1999). In this study, multiobjective linear programming is used to investigate the quantitative relationship between the underlying objectives. |
