Log In
Or create an account -> 
Imperial Library
  • Home
  • About
  • News
  • Upload
  • Forum
  • Help
  • Login/SignUp

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
  • ← Prev
  • Back
  • Next →
  • ← Prev
  • Back
  • Next →

Chief Librarian: Las Zenow <zenow@riseup.net>
Fork the source code from gitlab
.

This is a mirror of the Tor onion service:
http://kx5thpx2olielkihfyo4jgjqfb7zx7wxr3sd4xzt26ochei4m6f7tayd.onion