A First Course in Systems Biology

Cover
Half Title
Dedication
Title Page
Copyright Page
Table of Contents
Preface
Chapter 1: Biological Systems
Reductionism and Systems Biology
Even Simple Systems Can Confuse Us
Why Now?
Communicating Systems Biology
The Task Before Us
Exercises
References
Further Reading
Chapter 2: Introduction to Mathematical Modeling
Goals, Inputs, and Initial Exploration
2.1 Questions of Scale
2.2 Data Availability
Model Selection and Design
2.3 Model Structure
2.4 System Components
2.5 Model Equations
2.6 Parameter Estimation
Model Analysis and Diagnosis
2.7 Consistency and Robustness
2.8 Exploration and Validation of Dynamical Features
Model Use and Applications
2.9 Model Extensions and Refinements
2.10 Large-Scale Model Assessments
2.11 Questions of Design
2.12 Simplicity versus Complexity
Exercises
References
Further Reading
Chapter 3: Static Network Models
Strategies of Analysis
Interaction Graphs
3.1 Properties of Graphs
3.2 Small-World Networks
Dependencies Among Network Components
3.3 Causality Analysis
3.4 Mutual Information
Bayesian Reconstruction of Interaction Networks
3.5 Application to Signaling Networks
3.6 Applications to Other Biological Networks
Static Metabolic Networks and Their Analysis
3.7 Stoichiometric Networks
3.8 Variants of Stoichiometric Analysis
3.9 Metabolic Network Reconstruction
3.10 Metabolic Control Analysis
Exercises
References
Further Reading
Chapter 4: The Mathematics of Biological Systems
Discrete Linear Systems Models
4.1 Recursive Deterministic Models
4.2 Recursive Stochastic Models
Discrete Nonlinear Systems
Continuous Linear Systems
4.3 Linear Differential Equations
4.4 Linearized Models
Continuous Nonlinear Systems
4.5 Ad hoc Models
4.6 Canonical Models
4.7 More Complicated Dynamical Systems Descriptions
Standard Analyses of Biological Systems Models
4.8 Steady-State Analysis
4.9 Stability Analysis
4.10 Parameter Sensitivity
4.11 Analysis of Systems Dynamics
Other Attractors
4.12 Limit Cycles
4.13 Chaotic Attractors
Exercises
References
Further Reading
Chapter 5: Parameter Estimation
Parameter Estimation for Linear Systems
5.1 Linear Regression Involving a Single Variable
5.2 Linear Regression Involving Several Variables
Parameter Estimation for Nonlinear Systems
5.3 Comprehensive Grid Search
5.4 Nonlinear Regression
5.5 Genetic Algorithms
5.6 Other Stochastic Algorithms
5.7 Typical Challenges
Parameter Estimation for Systems of Differential Equations
Structure Identification
Exercises
References
Further Reading
Chapter 6: Gene Systems
The Central Dogma
Key Properties of DNA and RNA
6.1 Chemical and Physical Features
6.2 Size and Organization of DNA
6.3 Genes and Noncoding DNA
6.4 Eukaryotic DNA Packing
6.5 Epigenetics
RNA
6.6 Messenger RNA (mRNA)
6.7 Transfer RNA (tRNA)
6.8 Ribosomal RNA (rRNA)
6.9 Small RNAs
6.10 RNA Viruses
Gene Regulation
6.11 The lac Operon
6.12 Modes of Regulation
6.13 Transcription Factors
6.14 Models of Gene Regulation
Measuring Gene Expression
Localization of Gene Expression
Outlook
Exercises
References
Further Reading
Chapter 7: Protein Systems
Chemical and Physical Features of Proteins
7.1 Experimental Protein Structure Determination and Visualization
An Incomplete Survey of the Roles and Functions of Proteins
7.2 Enzymes
7.3 Transporters and Carriers
7.4 Signaling and Messenger Proteins
7.5 Proteins of the Immune System
7.6 Structure Proteins
Current Challenges in Protein Research
7.7 Proteomics
7.8 Structure and Function Prediction
7.9 Localization
7.10 Protein Activity and Dynamics
Exercises
References
Further Reading
Chapter 8: Metabolic Systems
Biochemical Reactions
8.1 Background
8.2 Mathematical Formulation of Elementary Reactions
8.3 Rate Laws
Pathways and Pathway Systems
8.4 Biochemistry and Metabolomics
8.5 Resources for Computational Pathway Analysis
8.6 Control of Pathway Systems
Methods of Metabolomic Data Generation
8.7 Sampling, Extraction, and Separation Methods
8.8 Detection Methods
8.9 Flux Analysis
From Data to Systems Models
8.10 Case Study 1: Analyzing Metabolism in an Incompletely Characterized Organism
8.11 Case Study 2: Metabolic Network Analysis
8.12 Case Study 3: Extraction of Dynamic Models from Experimental Data
Exercises
References
Further Reading
Chapter 9: Signaling Systems
Static Models of Signal Transduction Networks
9.1 Boolean Networks
9.2 Network Inference
Signal Transduction Systems Modeled with Differential Equations
9.3 Bistability and Hysteresis
9.4 Two-Component Signaling Systems
9.5 Mitogen-Activated Protein Kinase Cascades
9.6 Adaptation
9.7 Other Signaling Systems
Exercises
References
Further reading
Chapter 10: Population Systems
Population Growth
10.1 Traditional Models of Population Growth
10.2 More Complex Growth Phenomena
Population Dynamics Under External Perturbations
Analysis of Subpopulations
Interacting Populations
10.3 General Modeling Strategy
10.4 Phase-Plane Analysis
10.5 More Complex Models of Population Dynamics
Exercises
References
Further reading
Chapter 11: Integrative Analysis of Genome, Protein, and Metabolite Data: A Case Study in Yeast
On the Origin of Models
A Brief Review of the Heat Stress Response in Yeast
11.1 The Trehalose Cycle
Modeling Analysis of the Trehalose Cycle
11.2 Design and Diagnosis of a Metabolic Pathway Model
11.3 Analysis of Heat Stress
11.4 Accounting for Glucose Dynamics
11.5 Gene Expression
Multiscale Analysis
11.6 In Vivo NMR Profiles
11.7 Multiscale Model Design
11.8 The Trehalase Puzzle
Concluding Comments
Exercises
References
Further Reading
Chapter 12: Physiological Modeling: The Heart as an Example
Hierarchy of Scales and Modeling Approaches
12.1 Basics of Heart Anatomy
12.2 Modeling Targets at the Organ Level
12.3 Modeling Targets at the Tissue Level
12.4 Modeling Targets at the Cell Level
Simple Models of Oscillations
12.5 Black-Box Models of Oscillations
12.6 Summary of Black-Box Oscillation Models
12.7 From a Black Box to Meaningful Models
Electrochemistry in Cardiomyocytes
12.8 Biophysical Description of Electrochemical Processes at the Membrane of Cardiomyocytes
12.9 Resting Potentials and Action Potentials
12.10 Models of Action Potentials
12.11 Repeated Heartbeats
Issues of a Failing Heart
12.12 Modeling Heart Function and Failure Based on Molecular Events
Outlook for Physiological Multiscale Modeling
Exercises
References
Further Reading
Chapter 13: Systems Biology in Medicine and Drug Development
Are you Unique?
13.1 Biological Variability and Disease
13.2 Modeling Variability and Disease
Personalized Medicine and Predictive Health
13.3 Data Needs and Biomarkers
13.4 Personalizing Mathematical Models
The Drug Development Process
The Role of Systems Biology in Drug Development
13.5 Computational Target and Lead Identification
13.6 Receptor Dynamics
13.7 Pharmacokinetic Modeling
13.8 Pathway Screening with Dynamic Models
13.9 Emerging Roles of Systems Biology in Drug Development
Exercises
References
Further Reading
Chapter 14: Design of Biological Systems
Natural Design of Biological Systems
14.1 The Search for Structural Patterns
14.2 Network Motifs
14.3 Design Principles
14.4 Operating Principles
Goal-Oriented Manipulations and Synthetic Design of Biological Systems
14.5 Metabolic Engineering
14.6 Synthetic Biology
Case Studies of Synthetic Biological Systems Designs
14.7 Elementary Mode Analysis in Metabolic Engineering
14.8 Drug Development
14.9 Gene Circuits
The Future Has Begun
Exercises
References
Further Reading
Chapter 15: Emerging Topics in Systems Biology
Emerging Applications
15.1 From Neurons to Brains
15.2 Complex Diseases, Inflammation, and Trauma
15.3 Organisms and their Interactions with the Environment
Modeling Needs
15.4 Multiscale Modeling
15.5 A Data-Modeling Pipeline
Toward a Theory of Biology ... or Several Theories?
References
Further Reading
Glossary
Index