Quantitative Biology: A Practical Introduction

Description

This textbook is for biologists, to conduct quantitative analysis and modeling of biological processes at molecular and cellular levels. Focusing on practical concepts and techniques for everyday research, this text will enable beginners, both students and established biologists, to take the first step in quantitative biology. It also provides step-by-step tutorials to run various sample programs in one’s personal computer using Excel and Python. This volume traces topics, starting with an introductory chapter, such as modeling, construction and execution of numerical models, and key concepts in quantitative biology: feedback regulations, fluctuations and randomness, and statistical analyses. It also provide sample codes with guidance to procedure programming for actual biological processes such as movement of the nucleus within a cell, cell-cycle regulation, stripe pattern formation of skins, and distribution of energy. Written by a leading research scientist who has a background in biology, studied quantitative approaches by himself, and teaches quantitative biology at several universities, this textbook broadens quantitative approaches for biologists who do not have a strong background in mathematics, physics, or computer programming, and helps them progress further in their research. 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