Quantitative Biology: A Practical Introduction

Preface
Acknowledgments
Contents
1: Introduction to Quantitative Biology
	What You Will Learn in This Chapter
	1.1 What Is (Modern) Quantitative Biology?
		Questions
	1.2 Why Study Quantitative Biology?
		Questions
	1.3 The Aim and Target of This Book
	1.4 Construction of Quantitative Models as a Goal of Quantitative Biology
		1.4.1 What Kind of Model Is a Good Model?
		1.4.2 The Need for Quantitative Models
		1.4.3 How Can We Make a Good Quantitative Model?
			Questions
			Answers
			Take-Home Message
	References
		Further Reading
2: Cell Architectonics
	What You Will Learn in This Chapter
	2.1 Why We Deal with the Architectonics of the Cell (In This Book)?
	2.2 What Is Cell Architectonics?
	2.3 Objective #1: Mechanics of the Cell (Chap. 3)
	2.4 Objective #2: Diversity of the Cell (Chap. 7)
	2.5 Objective #3: Self-Organization of the Cell (Chap. 9)
	2.6 Objective #4: Development of the Cell over Time (Chap. 11)
		Take-Home Message
	Reference
		Further Reading
3: Mechanics of the Cell
	What You Will Learn in This Chapter
	3.1 Mechanical Forces and Cellular Dynamics
	3.2 Methods for Applying Force to Cellular Materials
	3.3 Mechanical Properties of Structures Inside the Cell
	3.4 Relationship Between Intracellular Deformation and Force: Elasticity, Viscosity, and Viscoelasticity
	3.5 Stress-Strain Relationship of Elastic Materials
	3.6 Rheology
	3.7 Reynolds Number
		Questions
	3.8 Equations for Describing Viscous Fluids
	3.9 Modeling Cell Behaviors Based on Cell Mechanics
		Answers
		Take-Home Message
	References
		Further Reading
4: Implementing Toy Models in Microsoft Excel
	What You Will Learn in This Chapter
	4.1 Custom Makes All Things Easy
	4.2 The Toy Model: Centration of the Nucleus Inside a Cell
		4.2.1 Biological Background
		4.2.2 Constructing One-Dimensional Model for Nuclear Centration
			4.2.2.1 Modeling Forces to Move the Nucleus Using Stokes´ Law
			4.2.2.2 Force Generation in the Cytoplasmic Pulling Model
			4.2.2.3 Force Generation in the Pushing Model
			4.2.2.4 Force Generation in the Cortex Pulling Model (an Educational Version)
	4.3 Calculating the Movement of the Nucleus
	4.4 Model Implementation in Microsoft Excel
		4.4.1 Implementation of Cytoplasmic Pulling Model
		4.4.2 Implementation of Pushing Model
		4.4.3 Implementation of Cortex Pulling Model
			Questions
			Answers
			Take-Home Message
	References
5: Implementing Toy Models in Python
	What You Will Learn in This Chapter
	5.1 Why Do We Need to Learn Programming?
	5.2 Why Python?
	5.3 Getting Started with Python
	5.4 A Code to Simulate Nuclear Centration
		Questions
		Answers
		Take-Home Message
	Reference
6: Differential Equations to Describe Temporal Changes
	What You Will Learn in This Chapter
	6.1 Why the Use of a Differential Equation?
		6.1.1 What Is a Differential Equation?
		6.1.2 Modeling a Biological Phenomenon Using Differential Equation
	6.2 What Differential Equations Convey
		6.2.1 Equilibrium Points
		6.2.2 Stability of the Equilibrium Points: Linear Stability Analysis
	6.3 Solving Differential Equations
		6.3.1 Modeling Nuclear Centration Using Differential Equation
		6.3.2 Analytical Solutions
			Questions
		6.3.3 Calculating the Consequences of Differential Equations Computationally: Euler and the Runge-Kutta Methods
			Questions
		6.3.4 A Coding Example of the Runge-Kutta Method with Python
			Answers
			Take-Home Message
	References
7: Diversity of the Cell
	What You Will Learn in This Chapter
	7.1 Diversity of the Cell
	7.2 Diversity in Cell Size: Scaling Problems
	7.3 Diversity in Cellular Response Due to Fluctuations
	7.4 Diversity in Cell Arrangement Due to Spatial Restrictions
	7.5 Diversity in the Pattern of Cytoplasmic Streaming Due to Molecular Activities
	7.6 The Role of a Gene as a Switch
		Take-Home Message
	References
8: Randomness, Diffusion, and Probability
	What You Will Learn in This Chapter
	8.1 Randomness
		8.1.1 Why Should We Consider Randomness for Biological Processes?
		8.1.2 Modeling Random Motion with Python
	8.2 Diffusion
		8.2.1 Random Motion and Diffusion
		8.2.2 Diffusion Equation
	8.3 Energy Landscape and Existing Probability
		8.3.1 Potential Energy and Energy Landscape
		8.3.2 Boltzmann Distribution
		8.3.3 Existing Probability
			Questions
			Answers
			Take-Home Message
	References
9: Self-Organization of the Cell
	What You Will Learn in This Chapter
	9.1 Why Self-Organization?
	9.2 Mechanisms to Create Order
	9.3 Negative Feedback Regulation
	9.4 Positive Feedback Regulation
		9.4.1 Positive Feedback Plus Fluctuations
		9.4.2 Positive Feedback Plus Negative Feedback
	9.5 Symmetry Breaking
	9.6 Phase Separation in Cell Biology
		Take-Home Message
	References
10: Modeling Feedback Regulations
	What You Will Learn in This Chapter
	10.1 Basic Knowledge to Model Feedback Regulations Using Differential Equation
		10.1.1 Modeling of Activation and Repression Using Hill Function
		10.1.2 Modeling Degradation
		10.1.3 Negative Feedback Regulations
			Questions
		10.1.4 Linear Stability Analyses for Negative Feedback Models
	10.2 Reaction-Diffusion Mechanism Creating Biological Patterns
		10.2.1 An Example of a Reaction-Diffusion System
		10.2.2 Linear Stability Analysis for the Reaction-Diffusion System
			Questions
			Answers
			Take-Home Message
	References
11: Development of the Cell over Time (Perspectives)
	What You Will Learn in This Chapter
	11.1 Development over Time: Temporal Changes from One Order to Another
	11.2 An Example: Development of Cell Arrangement over Time
	11.3 Models for Individual but Sequential Cell Orders
	11.4 Transition of Different Orders: Diversity in Time Scales
	11.5 Perspective
		Take-Home Message
	References
Index