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Computer simulation of biological systems

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The current status of mathematical models of biological systems is reviewed. Advances in supercomputer hardware allows more complex models to be constructed. The new generation of microcomputers are quite adequate for many computer simulations of biological systems. A theory of modeling is being developed to improve the relationship between the real biological system and the model. Deterministic models, stochastic models and applications of control theory and optimization methods are discussed. Examples given include models of molecular structure, of experimental techniques, and of biochemical reactions. It is recommended that experimental biologists consider the use of microcomputers to model the system under study as a part of their research program.

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References

  1. Sampson JR: Biological Information Processing: Current Theory and Computer Simulation. Wiley-Interscience, New York, 1984.

    Google Scholar 

  2. Segel LA: Mathematical Models in Molecular and Cellular Biology. Cambridge University Press, Cambridge, 1980.

    Google Scholar 

  3. Crecine JP: The next generation of personal computers. Science 231:931–943, 1986.

    Google Scholar 

  4. Zeigler BP: Theory of Modelling and Simulation. Wiley-Interscience, New York, 1976.

    Google Scholar 

  5. Lumb JR, MacFarland B: A computer simulation of the production of lymphocytes in the thymus: A preliminary report. J Reticuloendo Soc 12:80–89, 1972.

    Google Scholar 

  6. Lumb JR: A regenerating computer model of the thymus. Comput Biomed Res 8:379–392, 1975.

    Google Scholar 

  7. Zeigler BP: Structuring the organization of partial models. Int J Gen Systems 4:81–88, 1978.

    Google Scholar 

  8. Zeigler BP: Multi-level multi-formalism modeling, an ecosystem example. In: Halfon E (ed). Theoretical Ecosystems. Academic Press, New York, 1979, pp 17–54.

    Google Scholar 

  9. Zeigler BP: Simplification of biochemical reaction systems. In: Segel LA (ed). Mathematical Models in Molecular and Cellular Biology. Cambridge University Press, Cambridge, 1980, pp 112–145.

    Google Scholar 

  10. Zeigler BP: Multifacetted Modeling and Discrete Event Simulation. Academic Press, New York, 1984.

    Google Scholar 

  11. Bell GI: Mathematical model of clonal selection and antibody production. J Theoret Biol 29:191–232, 1970.

    Google Scholar 

  12. Bell GI: Mathematical model of clonal selection and antibody production, II. J Theoret Biol 33:339–378, 1971.

    Google Scholar 

  13. Bell GI: Mathematical model of clonal selection and antibody production, III. The cellular basis of immunological paralysis. J Theoret Biol 33:379–398, 1974.

    Google Scholar 

  14. Lumb JR, Morrison LM: A computer simulation of the cellular kinetics of the thymus-independent humoral immune response. Comput Biomed Res 14:220–231, 1981.

    Google Scholar 

  15. Perlson AM: Chaos. In: Segel LA (ed). Mathematical Models in Molecular and Cellular Biology. Cambridge University Press, Cambridge, 1980, pp 349–364.

    Google Scholar 

  16. DeLisi C, Hiernaux JRJ: Regulation of Immune Response Dynamics. CRC Press, Boca Raton, FL, 1982.

    Google Scholar 

  17. Levinthal C: Molecular model-building by computer. Sci Am 214(6):42–52, 1966.

    Google Scholar 

  18. Namba K, Caspar DAD, Stubbs GJ: Computer graphics representation of levels of organization in tobacco mosaic virus structure. Science 227:773–776, 1985.

    Google Scholar 

  19. Thiebaux HJ, Pattee HH: Statistical studies of protein sequences: Pair and triplet analysis in helical conformations. J Theoret Biol 17:121–135, 1967.

    Google Scholar 

  20. Valiquette G, Zimmermann EA, Roberts JL: mRNA sequence predictions from homologous protein sequences. J Theoret Biol 112:445–458, 1985.

    Google Scholar 

  21. Klopman G, Rosenkranz H: Structural requirements for the mutagenicity of environmental nitroarenes. Mut Res 126:227–238, 1984.

    Google Scholar 

  22. Klopman G, Contreras R: Use of artificial intelligence in structure-activity correlations of anticonvulsant drugs. Mol Pharm 27:86–93, 1985.

    Google Scholar 

  23. Klopman G, Macina OT: Use of the computer automated structure evaluation program in determining quantitative structure-activity relationships within hallucinogenic phenylalkylamines. J Theoret Biol 113:637–648, 1985.

    Google Scholar 

  24. Bier M, Palusinski OA, Mosher RA, Saville DA: Electrophoresis: Mathematical modeling and computer simulation. Science 219:1281–1287, 1983.

    Google Scholar 

  25. Perlson AM: Theory of immunoassays. In: Segel LA (ed). Mathematical Models in Molecular and Cellular Biology. Cambridge University Press, Cambridge, 1980, pp 423–439.

    Google Scholar 

  26. Priban I: Models in medicine. Science J 1968(6):61–67, 1968.

    Google Scholar 

  27. Grodins FS: General applicability of control theory to biological systems with some exemplification in the respiratory system. Fed Proc 28:47–51, 1969.

    Google Scholar 

  28. Rapp PE: Biological application of control theory. In: Segel LA (ed). Mathematical Models in Molecular and Cellular Biology. Cambridge University Press, Cambridge, 1980, pp 146–247.

    Google Scholar 

  29. Perlson AM: Applications of control theory in immunology. In: Segel LA (ed). Mathematical Models in Molecular and Cellular Biology. Cambridge University Press, Cambridge, 1980, pp 404–422.

    Google Scholar 

  30. Brady RM: Optimization strategies gleaned from biological evolution. Nature 317:804–806, 1985.

    Google Scholar 

  31. Garfinkel D, Garfinkel L, Pring M, Green S, Chance B: Computer application to biochemical kinetics. Ann Rev Biochem 39:473–498, 1970.

    Google Scholar 

  32. Garfinkel D, Kohn MC: In: Jacobus WE, Ingwall JS (eds). Heart Creatine Kinase. Williams and Wilkins, Baltimore, 1980.

  33. Palsson BO, Lightfoot EN: Mathematical modeling of dynamics and control in metabolic networks. I. On MichaelisMenten kinetics. J Theoret Biol 111:273–302, 1984.

    Google Scholar 

  34. Palsson BO, Jamier R, Lightfoot EN: Mathematical modeling of dynamics and control in metabolic networks. II. Simple dimeric enzymes. J Theoret Biol 111:303–321, 1984.

    Google Scholar 

  35. Palsson BO, Lightfoot EN: Mathematical modeling of dynamics and control in metabolic networks. IV. Local stability analysis of single biochemical control loops. J Theoret Biol 113:261–277, 1985.

    Google Scholar 

  36. Palsson BO, Lightfoot EN: Mathematical modeling of dynamics and control in metabolic networks. V. Static bifurcations in single biochemical control loops. J Theoret Biol 113:279–298, 1985.

    Google Scholar 

  37. Teasdale RD, Carr AR, Read RSD: Substrate aggregation and cooperation enzyme kinetics: Consideration of enzyme access with large aggregates. J Theoret Biol 114:375–382, 1985.

    Google Scholar 

  38. Eyring H, Lin SH, Lin SM: In: Basic Chemical Kinetics, Chapter 1. Wiley and Sons, New York, 1980.

  39. Delville A, Laszlo P, Nelson DJ: Calmodulin, calcium, potassium, and magnesium ion multiple equilibria and kinetics for interconversion, including the effect of repeated stimulation. J Theoret Biol 112:157–175, 1985.

    Google Scholar 

  40. Johnson HA: Information theory in biology after 18 years. Science 168:1545–1550, 1970.

    Google Scholar 

  41. Lumb JR: The value of theoretical models in immunological research. Immunol Today 4:209–210, 1983.

    Google Scholar 

  42. Maddox J: Aggregation by very large numbers. Nature 318:229, 1985.

    Google Scholar 

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Lumb, J.R. Computer simulation of biological systems. Mol Cell Biochem 73, 91–98 (1987). https://doi.org/10.1007/BF00219423

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  • DOI: https://doi.org/10.1007/BF00219423

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