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Analsis and Control Design for Signal Transduction Networks
|關鍵字:||signal transduction networks;訊息傳導網路;biochemical networks;systems biology;feedback linearization;Lyapunov stability;生化網路;系統生物;回授線性化;李亞普諾夫穩定性||出版社:||電機工程學系所||引用:|| B. S. Chen, Y. C. Wang, W. S. Wu and W. H. Li, A new measure of the robustness of biochemical networks, Bioinformatics, Vol. 21, pp. 2698-2705, 2005.  O. Wolkenhauer, B. K. Ghosh and K. H. Cho, Control and coordination in biochemical networks, Control Systems Magazine, IEEE, Vol. 24, pp. 30-34, 2004.  J. Saez-Rodriguez, A. Kremling, H. Conzelmann, K. Bettenbrock and E. D. Gilles, Modular analysis of signal transduction networks, Control Systems Magazine, IEEE, Vol. 24, pp. 35-52, 2004.  N. V. Torres and E. O. Voit, Pathway analysis and optimization in metabolic engineering, Cambridge University Press, 2002.  J. D. Murray, Mathematical Biology, Springer-Verlag, New York, 1993.  M. S. Calder and D. Siegel, Properties of the Michaelis-Menten mechanism in phase space, Journal of Mathematical Analysis and Applications, Vol. 339, pp. 1044-1064, 2008.  H. Conzelmann, J. Saez-Rodriguez, T. Sauter, E. Bullinger, F. Allgower and E. D. Gilles, Reduction of mathematical models of signal transduction networks: simulation-based approach applied to EGF receptor signalling, Systems Biology, Vol. 1, pp. 159-169, 2004.  H. Conzelmann, J. Saez-Rodriguez, T. Sauter, B. N. Kholodenko and E. D. Gilles, A domain-oriented approach to the reduction of combinatorial complexity in signal transduction networks, BMC Bioinformatics, Vol. 7, No. 34, 2006.  M. A. Savageau, Biochemical systems analysis: a study of function and design in molecular biology, The Quarterly Review of Biology, Vol. 52, pp. 292-293, 1977.  F. S. Wang, C. L. Ko and E. O. Voit, Kinetic modeling using S-systems and lin-log approaches, Biochemical Engineering Journal, Vol. 33, pp. 238-247, 2007.  E. O. Voit, Computational analysis of biochemical systems, Cambridge University Press, Cambridge, UK, 2000.  E. O. Voit, Canonical nonlinear modeling: S-systems approach to understanding complexity, Van Nostrand Reinhold, New York, 1991.  K. Zhou, Essentials of robust control, Prentice Hall, New Jersey, 1998.  C. T. Chen, Linear system theory and design, Oxford University Press, New York, 1998.  K. A. Hoo and J. C. Kantor, Global linearization and control of a mixed culture bioreactor with competition and external inhibition, Mathematical Biosciences, Vol. 82, pp. 43-62, 1986.  K. A. Hoo and J. C. Kantor, Linear feedback equivalence and control of an unstable biological reactor, Chemical Engineering Communications, Vol. 46, pp. 385-399, 1986.  B. Noble and J. W. Daniel, Applied linear algebra, Pearson Education Taiwan, Taiwan, 2003.  R. W. Brockett, Nonlinear systems and differential geometry, Proceedings of the IEEE, Vol. 64, pp. 61-72, 1976.  A. Ervadi-Radhakrishnan and E. O. Voit, Controllability of non-linear biochemical systems, Mathematical Biosciences, Vol. 196, pp. 99-123, 2005.  C. L. Lin, Mathematics of modern control theory, Kaun Tang international publications, Taipei, 2007.  M. A. Savageau, Design principles for elementary gene circuits: elements, methods and examples, Chaos, Vol. 11 pp. 142-159, 2001.  M. A. Savageau, Alternative designs for a genetic switch: analysis of switching times using the piece-wise power-law representation, Mathematical Biosciences, Vol. 180, pp. 237-253, 2002.  M. A. Savageau, Biochemical systems analysis, Journal of Theoretical Biology, Vol. 25, pp. 365-369, 1969.  E. O. Voit, M. A. Savageau, Accuracy of alternative representations for integrated biochemical systems, Biochemistry, Vol. 26, pp. 6869-6880, 1987.  A. Sorribas and M. A. Savageau, A comparison of variant theories of intact biochemical systems. 1. enzyme-enzyme interactions and biochemical systems Theory. Mathematical biosciences, Vol. 94, pp. 161-193, 1989.  M. A. Savageau, Parameter sensitivity as a criterion for evaluating and comparing the performance of biochemical systems, Nature, Vol. 229, pp.542-544, 1971  R. W. Brockett, Feedback invariants for nonlinear systems, Proceedings of the IFAC World Congress, Helsinki, pp. 1115-1120, 1978.  A. Isidori, Nonlinear control systems: an introduction, Springer, New York, 1995.  Q. Lu, Y. Sun and S. Mei, Nonlinear control systems and power system Dynamics, Kluwer Academic Publishers, 2001.  H. K. Khalil, Nonlinear systems, Pearson Education, New Jersey, 2002.  A. Sorribas and M. Cascante, Structure identifiability in metabolic pathways: parameter estimation in models based on the power-law formalism, Biochemical Journal, Vol. 298, pp. 303-311, 1994.||摘要:||
Signal transduction networks of biological systems are highly complex. How to mathematically describe a signal transduction network by systematic approaches so as to further develop an appropriate and effective control strategy is attractive to control engineers. In this thesis, a mathematical model and a controller design idea of signal transduction networks are presented. For constructing mathematical model, a new cascaded analysis model is proposed. Dynamic analysis, steady-state analysis, stability analysis, sensitivity analysis and controller design are simulated and fully verified. It is expected that this research could be a basis for constructing mathematical models and designing controllers for signal transduction networks in biological systems.
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