A first course in systems biology /

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This is a textbook designed for advanced undergraduate and graduate students. Its main focus is the development of computational models and their applications to diverse biological systems. Because the biological sciences have become so complex that no individual can acquire complete knowledge in an...

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Bibliographic Details
Main Author: Voit, Eberhard O.
Format: Printed Book
Language:English
Published: New York : Garland Science, �2013.
Subjects:
Systems biology.
Computational biology.
Systembiologie.
Table of Contents:
  • Machine generated contents note: ch. 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
  • ch. 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
  • ch. 3 Static Network Models
  • Strategies of Analysis
  • Interaction Graphs
  • 3.1. Properties of Graphs
  • 3.2. Small-World Networks.
  • Contents note continued: 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
  • ch. 4 The Mathematics of Biological Systems
  • Discrete Linear Systems Models
  • 4.1. Recursive Deterministic Models
  • 4.2. Recursive Stochastic Models
  • Continuous Linear Systems
  • 4.3. Linear Differential Equations
  • 4.4. Linearized Models
  • Discrete Nonlinear Systems
  • 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.
  • Contents note continued: 4.9. Stability Analysis
  • 4.10. Parameter Sensitivity
  • 4.11. Analysis of Systems Dynamics
  • Exercises
  • References
  • Further Reading
  • ch. 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
  • ch. 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).
  • Contents note continued: 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
  • ch. 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
  • ch. 8 Metabolic Systems
  • Biochemical Reactions
  • 8.1. Background.
  • Contents note continued: 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
  • ch. 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.
  • Contents note continued: 9.6. Other Signaling Systems
  • Exercises
  • References
  • Further Reading
  • ch. 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
  • ch. 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.
  • Contents note continued: 11.8. The Trehalase Puzzle
  • Concluding Comments
  • Exercises
  • References
  • Further Reading
  • ch. 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. Linear Oscillation Models
  • 12.6. Nonlinear Oscillation Models
  • 12.7. Summary of Black-Box Oscillation Models
  • 12.8. From a Black Box to a Meaningful Model
  • Electrochemistry in Cardiomyocytes
  • 12.9. Biophysical Description of Electrochemical Processes at the Membrane of Cardiomyocytes
  • 12.10. Resting Potentials and Action Potentials
  • 12.11. Models of Action Potentials
  • 12.12. Repeated Heartbeats
  • Issues of a Failing Heart
  • 12.13. Modeling Heart Function and Failure Based on Molecular Events
  • Outlook for Physiological Multiscale
  • Modeling.
  • Contents note continued: Exercises
  • References
  • Further Reading
  • ch. 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 Dynamical Models
  • 13.9. Emerging Roles of Systems Biology in Drug Development
  • Exercises
  • References
  • Further Reading
  • ch. 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.
  • Contents note continued: 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
  • ch. 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.

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