Mathematical Modeling for Life Sciences: A Primer (Lecture Notes on Mathematical Modelling in the Life Sciences)

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予約

Mathematical Modeling for Life Sciences: A Primer (Lecture Notes on Mathematical Modelling in the Life Sciences)

Santillan, Moises

ウェブストア価格 ¥15,076（本体¥13,706）
Springer, Berlin; Springer Nature Switzerland（2026/08発売）
外貨定価 EUR 53.50
ポイント 137pt

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製本 Hardcover:ハードカバー版
商品コード 9783032292636

Full Description

This textbook introduces mathematical modelling in life sciences in an interdisciplinary setting for students whose backgrounds range from medicine to mathematics, focusing on a set of topics that introduce mathematical thinking through biological questions. Each chapter begins with a clear biological question and then introduces the mathematical tools required to analyze it. This iterative approach is a proven success in the classrom. Starting with population dynamics, because its concepts are intuitive to students from the exact sciences, the text then broadens the canvas to topics such as electrophysiology and chemical kinetics, demonstrating the wide applicability of the same mathematical techniques. This structure is intended to build intuition alongside technical skill—students learn why a model is useful before learning how to build it.

Also included are short historical perspectives and vignettes about the development of key ideas. These historical contexts motivate students and help them better grasp why particular concepts matter and how they arose in response to real scientific problems.

Whether you are a student seeking a first rigorous introduction to mathematical biology or an instructor looking for a compact course text, this book is designed to be accessible, adaptable, and practical: you will encounter clear problems, worked mathematical tools, and exercises aimed at building modeling confidence and insight.

Chapter 1. On the Use of Models in Science.- Chapter 2. Why don't Clouds Fall?.- Chapter 3. From Ancient Math to Modern Science: The Fantastic Journey of the Exponential Function.- Chapter 4. Exponential Decay.- Chapter 5. Exponential Growth.- Chapter 6. Local Stability Analysis.- Chapter 7. On the Interconnected Origins of Statistics, Probability Theory and Population Dynamics.- Chapter 8. Logistic Model.- Chapter 9. Extending the logistic model.- Chapter 10. A Brief History of Nonlinear Dynamics.- Chapter 11. Local Stability Analysis in 2D Systems.- Chapter 12. Historical Origin of Population Ecology.- Chapter 13. Competitive Lotka-Volterra Model.- Chapter 14. SIR Model.- Chapter 15. A Matter of Scales.- Chapter 16. Simplified SIR Model.- Chapter 17. The Interdisciplinary Journey of Oscillators: From Transatlantic Navigation to Neurophysiology.- Chapter 18. The Damped Harmonic Oscillator.- Chapter 19. The van der Pol Oscillator.- Chapter 20. The FitzHugh-Nagumo Model.- Chapter 21. Frankenstein, Vitalism, and Complexity Science.- Chapter 22. Quasisteady State Approximation.- Chapter 23. Hematopoiesis Regulation.- Chapter 24. A.V. Hill and the Origins of Modern Biophysics.- Chapter 25. Ligand-Receptor Dynamics.- Chapter 26. The Interdisciplinary Origins of Molecular Biology.- Chapter 27. Gene Regulation.- Chapter 28. Mathematical Modelling of Simple BacterialGene Regulatory Networks.