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Index
Cover
Title Page
Copyright
Preface
Guide to Different Topics of the Book
About the Authors
Part One: Introduction to Systems Biology
1: Introduction
1.1 Biology in Time and Space
1.2 Models and Modeling
1.2.1 What Is a Model?
1.2.2 Purpose and Adequateness of Models
1.2.3 Advantages of Computational Modeling
1.3 Basic Notions for Computational Models
1.3.1 Model Scope
1.3.2 Model Statements
1.3.3 System State
1.3.4 Variables, Parameters, and Constants
1.3.5 Model Behavior
1.3.6 Model Classification
1.3.7 Steady States
1.3.8 Model Assignment is Not Unique
1.4 Networks
1.5 Data Integration
1.6 Standards
1.7 Model Organisms
1.7.1 Escherichia Coli
1.7.2 Saccharomyces Cerevisiae
1.7.3 Caenorhabditis Elegans
1.7.4 Drosophila Melanogaster
1.7.5 Mus Musculus
References
Further Reading
2: Modeling of Biochemical Systems
2.1 Overview of Common Modeling Approaches for Biochemical Systems
2.2 ODE Systems for Biochemical Networks
2.2.1 Basic Components of ODE Models
2.2.2 Illustrative Examples of ODE Models
References
Further Reading
3: Structural Modeling and Analysis of Biochemical Networks
3.1 Structural Analysis of Biochemical Systems
3.1.1 System Equations
3.1.2 Information Encoded in the Stoichiometric Matrix N
3.1.3 The Flux Cone
3.1.4 Elementary Flux Modes and Extreme Pathways
3.1.5 Conservation Relations – Null Space of NT
3.2 Constraint-Based Flux Optimization
3.2.1 Flux Balance Analysis
3.2.2 Geometric Interpretation of Flux Balance Analysis
3.2.3 Thermodynamic Constraints
3.2.4 Applications and Tests of the Flux Optimization Paradigm
3.2.5 Extensions of Flux Balance Analysis
Exercises
References
Further Reading
4: Kinetic Models of Biochemical Networks: Introduction
4.1 Reaction Kinetics and Thermodynamics
4.1.1 Kinetic Modeling of Enzymatic Reactions
4.1.2 The Law of Mass Action
4.1.3 Reaction Thermodynamics
4.1.4 Michaelis–Menten Kinetics
4.1.5 Regulation of Enzyme Activity by Effectors
4.1.6 Generalized Mass Action Kinetics
4.1.7 Approximate Kinetic Formats
4.1.8 Convenience Kinetics and Modular Rate Laws
4.2 Metabolic Control Analysis
4.2.1 The Coefficients of Control Analysis
4.2.2 The Theorems of Metabolic Control Theory
4.2.3 Matrix Expressions for Control Coefficients
4.2.4 Upper Glycolysis as Realistic Model Example
4.2.5 Time-Dependent Response Coefficients
Exercises
References
Further Reading
5: Data Formats, Simulation Techniques, and Modeling Tools
5.1 Simulation Techniques and Tools
5.1.1 Differential Equations
5.1.2 Stochastic Simulations
5.1.3 Simulation Tools
5.2 Standards and Formats for Systems Biology
5.2.1 Systems Biology Markup Language
5.2.2 BioPAX
5.2.3 Systems Biology Graphical Notation
5.3 Data Resources for Modeling of Cellular Reaction Systems
5.3.1 General-Purpose Databases
5.3.2 Pathway Databases
5.3.3 Model Databases
5.4 Sustainable Modeling and Model Semantics
5.4.1 Standards for Systems Biology Models
5.4.2 Model Semantics and Model Comparison
5.4.3 Model Combination
5.4.4 Model Validity
References
Further Reading
6: Model Fitting, Reduction, and Coupling
Introduction
6.1 Parameter Estimation
6.1.1 Regression, Estimators, and Maximal Likelihood
6.1.2 Parameter Identifiability
6.1.3 Bootstrapping
6.1.4 Bayesian Parameter Estimation
6.1.5 Probability Distributions for Rate Constants
6.1.6 Optimization Methods
6.2 Model Selection
6.2.1 What Is a Good Model?
6.2.2 The Problem of Model Selection
6.2.3 Likelihood Ratio Test
6.2.4 Selection Criteria
6.2.5 Bayesian Model Selection
6.3 Model Reduction
6.3.1 Model Simplification
6.3.2 Reduction of Fast Processes
6.3.3 Quasi-Equilibrium and Quasi-Steady State
6.3.4 Global Model Reduction
6.4 Coupled Systems and Emergent Behavior
6.4.1 Modeling of Coupled Systems
6.4.2 Combining Rate Laws into Models
6.4.3 Modular Response Analysis
6.4.4 Emergent Behavior in Coupled Systems
6.4.5 Causal Interactions and Global Behavior
Exercises
References
Further Reading
7: Discrete, Stochastic, and Spatial Models
7.1 Discrete Models
7.1.1 Boolean Networks
7.1.2 Petri Nets
7.2 Stochastic Modeling of Biochemical Reactions
7.2.1 Chance in Biochemical Reaction Systems
7.2.2 The Chemical Master Equation
7.2.3 Stochastic Simulation
7.2.4 Chemical Langevin Equation and Chemical Noise
7.2.5 Dynamic Fluctuations
7.2.6 From Stochastic to Deterministic Modeling
7.3 Spatial Models
7.3.1 Types of Spatial Models
7.3.2 Compartment Models
7.3.3 Reaction–Diffusion Systems
7.3.4 Robust Pattern Formation in Embryonic Development
7.3.5 Spontaneous Pattern Formation
7.3.6 Linear Stability Analysis of the Activator–Inhibitor Model
Exercises
References
Further Reading
8: Network Structure, Dynamics, and Function
8.1 Structure of Biochemical Networks
8.1.1 Random Graphs
8.1.2 Scale-Free Networks
8.1.3 Connectivity and Node Distances
8.1.4 Network Motifs and Significance Tests
8.1.5 Explanations for Network Structures
8.2 Regulation Networks and Network Motifs
8.2.1 Structure of Transcription Networks
8.2.2 Regulation Edges and Their Steady-State Response
8.2.3 Negative Feedback
8.2.4 Adaptation Motif
8.2.5 Feed-Forward Loops
8.3 Modularity and Gene Functions
8.3.1 Cell Functions Are Reflected in Structure, Dynamics, Regulation, and Genetics
8.3.2 Metabolic Pathways and Elementary Modes
8.3.3 Epistasis Can Indicate Functional Modules
8.3.4 Evolution of Function and Modules
8.3.5 Independent Systems as a Tacit Model Assumption
8.3.6 Modularity and Biological Function Are Conceptual Abstractions
Exercises
References
Further Reading
9: Gene Expression Models
9.1 Mechanisms of Gene Expression Regulation
9.1.1 Transcription Factor-Initiated Gene Regulation
9.1.2 General Promoter Structure
9.1.3 Prediction and Analysis of Promoter Elements
9.1.4 Posttranscriptional Regulation through microRNAs
9.2 Dynamic Models of Gene Regulation
9.2.1 A Basic Model of Gene Expression and Regulation
9.2.2 Natural and Synthetic Gene Regulatory Networks
9.2.3 Gene Expression Modeling with Stochastic Equations
9.3 Gene Regulation Functions
9.3.1 The Lac Operon in E. coli
9.3.2 Gene Regulation Functions Derived from Equilibrium Binding
9.3.3 Thermodynamic Models of Promoter Occupancy
9.3.4 Gene Regulation Function of the Lac Promoter
9.3.5 Inferring Transcription Factor Activities from Transcription Data
9.3.6 Network Component Analysis
9.3.7 Correspondences between mRNA and Protein Levels
9.4 Fluctuations in Gene Expression
9.4.1 Stochastic Model of Transcription and Translation
9.4.2 Intrinsic and Extrinsic Variability
9.4.3 Temporal Fluctuations in Gene Cascades
Exercises
References
Further Reading
10: Variability, Robustness, and Information
10.1 Variability and Biochemical Models
10.1.1 Variability and Uncertainty Analysis
10.1.2 Flux Sampling
10.1.3 Elasticity Sampling
10.1.4 Propagation of Parameter Variability in Kinetic Models
10.1.5 Models with Parameter Fluctuations
10.2 Robustness Mechanisms and Scaling Laws
10.2.1 Robustness in Biochemical Systems
10.2.2 Robustness by Backup Elements
10.2.3 Feedback Control
10.2.4 Perfect Robustness by Structure
10.2.5 Scaling Laws
10.2.6 Time Scaling, Summation Laws, and Robustness
10.2.7 The Role of Robustness in Evolution and Modeling
10.3 Adaptation and Exploration Strategies
10.3.1 Information Transmission in Signaling Pathways
10.3.2 Adaptation and Fold-Change Detection
10.3.3 Two Adaptation Mechanisms: Sensing and Random Switching
10.3.4 Shannon Information and the Value of Information
10.3.5 Metabolic Shifts and Anticipation
10.3.6 Exploration Strategies
Exercises
References
Further Reading
11: Optimality and Evolution
11.1 Optimality in Systems Biology Models
11.1.1 Mathematical Concepts for Optimality and Compromise
11.1.2 Metabolism Is Shaped by Optimality
11.1.3 Optimality Approaches in Metabolic Modeling
11.1.4 Metabolic Strategies
11.1.5 Optimal Metabolic Adaptation
11.2 Optimal Enzyme Concentrations
11.2.1 Optimization of Catalytic Properties of Single Enzymes
11.2.2 Optimal Distribution of Enzyme Concentrations in a Metabolic Pathway
11.2.3 Temporal Transcription Programs
11.3 Evolution and Self-Organization
11.3.1 Introduction
11.3.2 Selection Equations for Biological Macromolecules
11.3.3 The Quasispecies Model: Self-Replication with Mutations
11.3.4 The Hypercycle
11.3.5 Other Mathematical Models of Evolution: Spin Glass Model
11.3.6 The Neutral Theory of Molecular Evolution
11.4 Evolutionary Game Theory
11.4.1 Social Interactions
11.4.2 Game Theory
11.4.3 Evolutionary Game Theory
11.4.4 Replicator Equation for Population Dynamics
11.4.5 Evolutionarily Stable Strategies
11.4.6 Dynamical Behavior in the Rock–Scissors–Paper Game
11.4.7 Evolution of Cooperative Behavior
11.4.8 Compromises between Metabolic Yield and Efficiency
Exercises
References
Further Reading
12: Models of Biochemical Systems
12.1 Metabolic Systems
12.1.1 Basic Elements of Metabolic Modeling
12.1.2 Toy Model of Upper Glycolysis
12.1.3 Threonine Synthesis Pathway Model
12.2 Signaling Pathways
12.2.1 Function and Structure of Intra- and Intercellular Communication
12.2.2 Receptor–Ligand Interactions
12.2.3 Structural Components of Signaling Pathways
12.2.4 Analysis of Dynamic and Regulatory Features of Signaling Pathways
12.3 The Cell Cycle
12.3.1 Steps in the Cycle
12.3.2 Minimal Cascade Model of a Mitotic Oscillator
12.3.3 Models of Budding Yeast Cell Cycle
12.4 The Aging Process
12.4.1 Evolution of the Aging Process
12.4.2 Using Stochastic Simulations to Study Mitochondrial Damage
12.4.3 Using Delay Differential Equations to Study Mitochondrial Damage
Exercises
References
Part Two: Reference Section
13: Cell Biology
13.1 The Origin of Life
13.2 Molecular Biology of the Cell
13.2.1 Chemical Bonds and Forces Important in Biological Molecules
13.2.2 Functional Groups in Biological Molecules
13.2.3 Major Classes of Biological Molecules
13.3 Structural Cell Biology
13.3.1 Structure and Function of Biological Membranes
13.3.2 Nucleus
13.3.3 Cytosol
13.3.4 Mitochondria
13.3.5 Endoplasmic Reticulum and Golgi Complex
13.3.6 Other Organelles
13.4 Expression of Genes
13.4.1 Transcription
13.4.2 Processing of the mRNA
13.4.3 Translation
13.4.4 Protein Sorting and Posttranslational Modifications
13.4.5 Regulation of Gene Expression
Exercises
References
Further Reading
14: Experimental Techniques
14.1 Restriction Enzymes and Gel Electrophoresis
14.2 Cloning Vectors and DNA Libraries
14.3 1D and 2D Protein Gels
14.4 Hybridization and Blotting Techniques
14.4.1 Southern Blotting
14.4.2 Northern Blotting
14.4.3 Western Blotting
14.4.4 In Situ Hybridization
14.5 Further Protein Separation Techniques
14.5.1 Centrifugation
14.5.2 Column Chromatography
14.6 Polymerase Chain Reaction
14.7 Next-Generation Sequencing
14.8 DNA and Protein Chips
14.8.1 DNA Chips
14.8.2 Protein Chips
14.9 RNA-Seq
14.10 Yeast Two-Hybrid System
14.11 Mass Spectrometry
14.12 Transgenic Animals
14.12.1 Microinjection and ES Cells
14.12.2 Genome Editing Using ZFN, TALENs, and CRISPR
14.13 RNA Interference
14.14 ChIP-on-Chip and ChIP-PET
14.15 Green Fluorescent Protein
14.16 Single-Cell Experiments
14.17 Surface Plasmon Resonance
Exercises
References
15: Mathematical and Physical Concepts
15.1 Linear Algebra
15.1.1 Linear Equations
15.1.2 Matrices
15.2 Dynamic Systems
15.2.1 Describing Dynamics with Ordinary Differential Equations
15.2.2 Linearization of Autonomous Systems
15.2.3 Solution of Linear ODE Systems
15.2.4 Stability of Steady States
15.2.5 Global Stability of Steady States
15.2.6 Limit Cycles
15.3 Statistics
15.3.1 Basic Concepts of Probability Theory
15.3.2 Descriptive Statistics
15.3.3 Testing Statistical Hypotheses
15.3.4 Linear Models
15.3.5 Principal Component Analysis
15.4 Stochastic Processes
15.4.1 Chance in Physical Theories
15.4.2 Mathematical Random Processes
15.4.3 Brownian Motion as a Random Process
15.4.4 Markov Processes
15.4.5 Markov Chains
15.4.6 Jump Processes in Continuous Time
15.4.7 Continuous Random Processes
15.4.8 Moment-Generating Functions
15.5 Control of Linear Dynamical Systems
15.5.1 Linear Dynamical Systems
15.5.2 System Response and Linear Filters
15.5.3 Random Fluctuations and Spectral Density
15.5.4 The Gramian Matrices
15.5.5 Model Reduction
15.5.6 Optimal Control
15.6 Biological Thermodynamics
15.6.1 Microstate and Statistical Ensemble
15.6.2 Boltzmann Distribution and Free Energy
15.6.3 Entropy
15.6.4 Equilibrium Constant and Energies
15.6.5 Chemical Reaction Systems
15.6.6 Nonequilibrium Reactions
15.6.7 The Role of Thermodynamics in Systems Biology
15.7 Multivariate Statistics
15.7.1 Planning and Designing Experiments for Case-Control Studies
15.7.2 Tests for Differential Expression
15.7.3 Multiple Testing
15.7.4 ROC Curve Analysis
15.7.5 Clustering Algorithms
15.7.6 Cluster Validation
15.7.7 Overrepresentation and Enrichment Analyses
15.7.8 Classification Methods
Exercises
References
16: Databases
16.1 General-Purpose Data Resources
16.1.1 PathGuide
16.1.2 BioNumbers
16.2 Nucleotide Sequence Databases
16.2.1 Data Repositories of the National Center for Biotechnology Information
16.2.2 GenBank/RefSeq/UniGene
16.2.3 Entrez
16.2.4 EMBL Nucleotide Sequence Database
16.2.5 European Nucleotide Archive
16.2.6 Ensembl
16.3 Protein Databases
16.3.1 UniProt/Swiss-Prot/TrEMBL
16.3.2 Protein Data Bank
16.3.3 Panther
16.3.4 InterPro
16.3.5 iHOP
16.4 Ontology Databases
16.4.1 Gene Ontology
16.5 Pathway Databases
16.5.1 Kegg
16.5.2 Reactome
16.5.3 ConsensusPathDB
16.5.4 WikiPathways
16.6 Enzyme Reaction Kinetics Databases
16.6.1 Brenda
16.6.2 Sabio-Rk
16.7 Model Collections
16.7.1 BioModels
16.7.2 JWS Online
16.8 Compound and Drug Databases
16.8.1 Chebi
16.8.2 Guide to Pharmacology
16.9 Transcription Factor Databases
16.9.1 Jaspar
16.9.2 Tred
16.9.3 Transcription Factor Encyclopedia
16.10 Microarray and Sequencing Databases
16.10.1 Gene Expression Omnibus
16.10.2 ArrayExpress
References
17: Software Tools for Modeling
17.1 13C-Flux2
17.2 Antimony
17.3 Berkeley Madonna
17.4 Biocham
17.5 BioNetGen
17.6 Biopython
17.7 BioTapestry
17.8 BioUML
17.9 CellDesigner
17.10 CellNetAnalyzer
17.11 Copasi
17.12 CPN Tools
17.13 Cytoscape
17.14 E-Cell
17.15 EvA2
17.16 FEniCS Project
17.17 Genetic Network Analyzer (GNA)
17.18 Jarnac
17.19 JDesigner
17.20 JSim
17.21 Knime
17.22 libSBML
17.23 MASON
17.24 Mathematica
17.25 MathSBML
17.26 Matlab
17.27 MesoRD
17.28 Octave
17.29 Omix Visualization
17.30 OpenCOR
17.31 Oscill8
17.32 PhysioDesigner
17.33 PottersWheel
17.34 PyBioS
17.35 PySCeS
17.36 R
17.37 SAAM II
17.38 SBMLeditor
17.39 SemanticSBML
17.40 SBML-PET-MPI
17.41 SBMLsimulator
17.42 SBMLsqueezer
17.43 SBML Toolbox
17.44 SBtoolbox2
17.45 SBML Validator
17.46 SensA
17.47 SmartCell
17.48 STELLA
17.49 STEPS
17.50 StochKit2
17.51 SystemModeler
17.52 Systems Biology Workbench
17.53 Taverna
17.54 Vanted
17.55 Virtual Cell (VCell)
17.56 xCellerator
17.57 Xppaut
Exercises
References
Index
End User License Agreement
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