Quantifying Life : A Symbiosis of Computation, Mathematics, and Biology /

Since the time of Isaac Newton, physicists have used mathematics to describe the behavior of matter of all sizes, from subatomic particles to galaxies. In the past three decades, as advances in molecular biology have produced an avalanche of data, computational and mathematical techniques have also...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Kondrashov, Dmitry A. (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Chicago : University of Chicago Press, [2016]
Temas:
Biology > Mathematical models.
Biology-Mathematical models.
Computational biology.
Mathematical models.
SCIENCE / General.
mathematical modeling, physics, biology, science, molecules, quantitative, coding, math, undergraduate, career, computational projects, programming, r language, variables, genetics, graphs, plotting, scripts, functions, biochemical reactions, probability, distribution, random numbers, loops, central limit theorem, independence, hypothesis testing, bayes formula, linear regression, fitting, log transforms, nonfiction, markov, molecular evolution, chaos, fixed points.
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Frontmatter
  • Contents
  • Preface
  • Chapter 0. Introduction
  • Part I. Describing single variables
  • Chapter 1. Arithmetic and variables: the lifeblood of modeling
  • Chapter 2. Functions and their graphs
  • Chapter 3. Describing data sets
  • Chapter 4. Random variables and distributions
  • Chapter 5. Estimation from a random sample
  • Part II. Relationship between two variables
  • Chapter 6. Independence of random variables
  • Chapter 7. Bayes' amazing formula
  • Chapter 8. Linear regression and correlation
  • Chapter 9. Nonlinear data fitting
  • Part III. Chains of random variables
  • Chapter 10. Markov models with discrete states
  • Chapter 11. Probability distributions of Markov chains
  • Chapter 12. Stationary distributions of Markov chains
  • Chapter 13. Dynamics of Markov models
  • Part IV. Variables that change with time
  • Chapter 14. Linear difference equations
  • Chapter 15. Linear ordinary differential equations
  • Chapter 16. Graphical analysis of ordinary differential equations
  • Chapter 17. Chaos and bifurcations in difference equations
  • Bibliography
  • Index

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