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T. Bäck and H.-P. Schwefel. An overview of evolutionary algorithms for parameter optimization. Evolutionary Computation. 1. 1–23. 1997.

T. Bäck, D.B. Fogel, and Z. Michalewicz. Handbook of evolutionary computation. Oxford: IOP Publishing/Oxford University Press. 1997.

M. Bell and M.C. Pike. Remark on algorithm 178 direct search. Communications of the Association for Computing Machinery. 9. 684–685. 1966.

G. Benettin, L. Galgani, A. Giorgilli and J.-M. Strelcyn. Lyapunov Characteristic Exponents for smooth dynamical systems and for Hamiltonian systems; A method for computing all of them. Part 2: Numerical application. Meccanica. 15. 21–30. 1980.

P.R. Brent. A new algorithm for minimizing a function of several variables without calculating derivatives. In Algorithms for minimization without derivatives, (Englewood Cliffs, NJ: Prentice-Hall, Inc.). 117–167. 1973.

J.A. Burns, A. Cornish-Bowden, A.K. Groen, R. Heinrich, H. Kacser, J.W. Porteous, S.M. Rapoport, T.A. Rapoport, J.W. Stucki, J.M. Tager, R.J.A Wanders, and H.V. Westerhoff. Control of metabolic systems. Trends in Biochemical Sciences. 10. 16. 1985.

Y. Cao, D. T. Gillespie and L. R. Petzold Adaptive explicit-implicit tau-leaping method with automatic tau selection Journal of Chemical Physics. 126. 224101. 2007.

A. Corana, M. Marchesi, C. Martini, and S. Ridella. Minimizing multimodal functions of continuous variables with the "simulated annealing" algorithm. ACM Transactions on Mathematical Software. 13. 262–280. 1987.

J. E. Dennis, D. M. Gay, and R. E. Welsch. An adaptive nonlinear least-squares algorithm. ACM Transactions on Mathematical Software. 7. 348–368. 1981.

J. E. Dennis, D. M. Gay, and R. E. Welsch. Algorithm 573: NL2SOL—An Adaptive Nonlinear Least-Squares Algorithm [E4] ACM Transactions on Mathematical Software. 7. 369–383. 1981.

P. Deuflhard and J. Heroth. Dynamic dimension reduction in ODE models. In Scientific Computing in Chemical Engineering, (F. Keil et al. Springer). 29–43. 1996.

R. Fletcher. Practical methods of optimization. 2nd Edition. Chichester: John Wiley & Sons. 1987.

D.B. Fogel, L.J. Fogel, and J.W. Atmar. Meta-evolutionary programming. 25th Asiloma Conference on Signals, Systems and Computers. IEEE Computer Society, Asilomar . 540–545. 1992.

M.A. Gibson and J. Bruck. Efficient Exact Stochastic Simulation of Chemical Systems with Many Species and Many Channels. Journal of Physical Chemistry. A104(9). 1876–1889. 2000.

C. Giersch. Control analysis of metabolic networks. 1. Homogeneous functions and the summation theorems for control coefficients. European Journal of Biochemistry. 174. 509–513. 1988.

P.E. Gill, W. Murray, and M.H. Wright. Practical Optimization. London, Academic Press. 1981.

D.T. Gillespie. A General Method for Numerically Simulating the Stochastic Time Evolution of Coupled Chemical Reactions. Journal of Computational Physics. 22. 403–434. 1976.

D.T. Gillespie. Approximate accelerated stochastic simulation of chemically reacting systems. J. Comp. Phys. 115, 1716. 2001.

D.E. Goldberg. Genetic algorithms in search, optimization and machine learning. Addison-Wesley, Reading, Mass. 1989.

G.H. Golub and C.F. van Loan. Matrix computations. Baltimore, 3rd Ed. Johns Hopkins Press. 1996.

R. Heinrich and T.A. Rapoport. A linear steady-state treatment of enzymatic chains. General properties, control and effector strength. European Journal of Biochemistry. 42. 89–95. 1974.

R. Heinrich and T.A. Rapoport. Mathematical analysis of multienzyme systems. II. Steady-state and transient control. BioSystems. 7. 130–136. 1975.

A.C. Hindmarsh. ODEPACK, A Systematized Collection of ODE Solvers. Scientific Computing, R. S. Stepleman et al. (eds.), North-Holland, Amsterdam, IMACS Transactions on Scientific Computation. 1. 55–64. 1983.

R. Hooke and T. A. Jeeves. "Direct search" solution of numerical and statistical problems. Journal of the Association for Computing Machinery. 8. 212–229. 1961.

H. Kacser and J.A. Burns. The control of flux. Symp. Soc. Exp. Biol.. 27. 65–104. 1973.

Kaupe. Algorithm 178 direct search. Communications of the Association of Computing Machinery. 6. 313–314. 1963.

J. Kennedy and R. Eberhart. Particle Swarm Optimization. Proceedings of the Fourth IEEE International Conference on Neural Networks, Perth, Australia. 1942–1948. 1995.

S. Kirkpatrick, J., C.D. Gelatt, and M. P. Vecchi. Optimization by simulated annealing. Science. 220. 671–680. 1983.

H. Lam. Using CSP to Understand Complex Chemical Kinetics. Combustion Science and Technology. 89. 375–404. 1993.

K. Levenberg. A method for the solution of certain nonlinear problems in least squares. Quart. Appl. Math.. 2. 164–168. 1944.

W.L. Maier. A Fast Pseudo Random Number Generator. Dr. Dobb's Journal. May. 152–157. 1991.

D.W. Marquardt. An algorithm for least squares estimation of nonlinear parameters. SIAM Journal. 11. 431–441. 1963.

M. Matsumoto and T. Nishimura. Mersenne twister: A 623-dimensionally equidistributed uniform pseudorandom number generator. ACM Transactions on Modeling and Computer Simulations . 8. 3–30. 1998.

Z. Michalewicz. Genetic algorithms + data structures = evolution programs. 3rd Edition. Springer-Verlag, Berlin. 1994.

M. Mitchell. An Introduction to Genetic Algorithms. MIT Press, Boston. 1995.

S. G. Nash. Newton-type minimization via the Lanczos method. SIAM Journal of Numerical Analysis. 21. 770–788. 1984.

J. A. Nelder and R. Mead. A simplex method for function minimization. Computer Journal. 7. 308–313. 1965.

L. Petzold. Automatic selection of methods for solving stiff and nonstiff systems of ordinary differential equations. SIAM J. Sci. Stat. Comput. 4. 136–148. 1983.

M.J.D. Powell. An efficient method for finding the minimum of a function of several variables without calculating derivatives. Computer Journal. 7. 155–162. 1964.

C. Reder. Metabolic control theory: a structural approach. Journal of Theoretical Biology. 135. 175–201. 1988.

T. Runarsson and X. Yao. Stochastic ranking for constrained evolutionary optimization. IEEE Transactions on Evolutionary Computation. 4. 284–294. 2000.

I. Shimada and T. Nagashima. A numerical approach to ergodic problem of dissipative dynamical systems. Progress of Theoretical Physics. 61. 1605–1616. 1979.

I. Surovtsova, N. Simus, Th. Lorenz, A. König, S. Sahle and U. Kummer. Accessible Methods for the Dynamic Time-scale Decomposition of Biochemical Systems. Bioinformatics 25. 2816–2823. 2009.

W.H. Swann. Direct search methods. Numerical methods for unconstrained optimization., W. Murray, ed. (London & New York: Academic Press). 13–28. 1972.

R. R. Vallabhajosyula, V. Chickarmane, and H. M. Sauro. Conservation analysis of large biochemical networks. Bioinformatics. 22. 346–353. 2006.

H.V. Westerhoff and Y.-D. Chen. How do enzyme activities control species concentrations? An additional theorem in the theory of metabolic control. European Journal of Biochemistry. 142. 425–430. 1984.

A. Wolf, J. B. Swift, H. Swinney, and J. A. Vastano. Determining Lyapunov exponents from a time series. Physica. 16D. 285–317. 1985.

J. Zobeley et al. A new time-dependent complexity reduction method for biochemical systems. In Transactions on Computational Systems (C. Prami et al., Springer). 90–110. 2005.