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Some Mathematical Tools

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Part of the book series: Undergraduate Texts in Mathematics ((UTM))

Abstract

This book is about biological modeling—the construction of mathematical abstractions intended to characterize biological phenomena and the derivation of predictions from these abstractions under real or hypothesized conditions. Amodel must capture the essence of an event or process but at the same time not be so complicated as to be intractable or to otherwise dilute its most important features. In this regard, differential equations have been widely invoked across the broad spectrum of biological modeling. Future values of the variables that describe a process depend on their rates of growth or decay. These in turn depend on present, or past, values of these same variables through simple linear or power relationships. These are the ingredients of a differential equation. We discuss linear and power laws between variables and their derivatives in Section 2.1 and differential equations in Section 2.4.

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References and Suggested Further Reading

  1. HIV/AIDS Surveillance Report, Division of HIV/AIDS, Centers for Disease Control, U.S. Department of Health and Human Services, Atlanta, GA, July, 1993.

    Google Scholar 

  2. S.A. Colgate, E.A. Stanley, J.M. Hyman, S.P. Layne, and C. Qualls, Risk-behavior model of the cubic growth of acquired immunodeficiency syndrome in the United States, Proc. Nat. Acad. Sci. USA, 86 (1989), 4793–4797.

    Article  Google Scholar 

  3. S. R. Williams, Nutrition and Diet Therapy, 2nd ed., Mosby, St. Louis, 1973, 655.

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  4. P. B. Sparling, M. Millard-Stafford, L. B. Rosskopf, L. Dicarlo, and B. T. Hinson, Body composition by bioelectric impedance and densitometry in black women, Amer. J. Human Biol., 5 (1993), 111–117.

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  5. E. Kamke, Differentialgleichungen Lösungsmethoden und Lösungen, Chelsea, New York, 1948.

    MATH  Google Scholar 

  6. R. Hogg and A. Craig, Introduction to Mathematical Statistics, Macmillan, New York, 1965.

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  7. Epidemiology Report IX (Number 2) Alabama Department of Public Health, Montgomery, AL, February, 1994.

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  8. R. P. Grimaldi, Discrete and Combinatorial Mathematics, Addison–Wesley, New York, 1998.

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Correspondence to Ronald W. Shonkwiler .

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© 2009 Springer-Verlag New York

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Shonkwiler, R.W., Herod, J. (2009). Some Mathematical Tools. In: Mathematical Biology. Undergraduate Texts in Mathematics. Springer, New York, NY. https://doi.org/10.1007/978-0-387-70984-0_2

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