Systems Biology.
Systems biology is a relatively new biological study field that focuses on the systematic study of complex interactions in biological systems, thus using a new perspective (integration instead of reduction) to study them. Particularly from year 2000 onwards, the term is used widely in the bioscience...
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Format: | eBook |
Language: | English |
Edition: | 1st ed. |
Imprint: | Somerset : John Wiley & Sons, Incorporated, 2012. |
Series: | Current Topics from the Encyclopedia of Molecular Cell Biology and Molecular Medicine Ser.
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Subjects: | |
Local Note: | Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2022. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries. |
Online Access: | Click to View |
Table of Contents:
- Intro
- Systems Biology
- Contents
- Preface and Commentary
- List of Contributors
- Part I Biological Basis of Systems Biology
- 1 Systems Biology
- 1 Introduction
- 2 What Is Systems Understanding?
- 3 Why Are Biological Systems Different?
- 3.1 Biological Complexity
- 3.2 Global Properties of Biological Systems
- 4 Systems Biology Modeling
- 4.1 Network Biology
- 4.2 Dynamic Network Models
- 4.3 Reaction-Diffusion Models
- 4.4 Holism versus Reductionism: The Global Dynamics of Networks
- 4.5 Modeling Resources and Standards
- 5 Future Prospects of Systems Biology
- 5.1 Synthetic Biology
- 5.2 Conclusions: Where Are We?
- References
- 2 Developmental Cell Biology
- 1 Historical Perspective
- 1.1 Origins of Cell Biology
- 1.2 Origins of Developmental Biology
- 1.3 Relationship between Cell and Developmental Biology
- 2 Cell Activities Underlying Development
- 2.1 Intracellular Signal Transduction
- 2.2 Cell Signaling
- 2.3 Cell-Cell Interactions
- 2.4 Cell-Matrix Interaction
- 3 Cell Differentiation
- 4 The Cell Cycle and Development
- 5 Organogenesis
- 6 Stem Cells
- 7 Chimeras
- 8 microRNAs (miRNAs)
- 9 In vitro Fertilization
- References
- 3 Principles and Applications of Embryogenomics
- 1 Introduction
- 2 Approaches
- 2.1 Overview
- 2.2 Large-Scale Analysis of Gene Expression at the Transcriptome Level
- 2.3 Cell-Cell Interactions
- 2.4 Cell-Matrix Interaction
- 3 Cell Differentiation
- 4 The Cell Cycle and Development
- 5 Organogenesis
- 6 Stem Cells
- 7 Chimeras
- 8 microRNAs (miRNAs)
- 9 In vitro Fertilization
- References
- 3 Principles and Applications of Embryogenomics
- 1 Introduction
- 2 Approaches
- 2.1 Overview
- 2.2 Large-Scale Analysis of Gene Expression at the Transcriptome Level
- 2.3 Large-Scale Analysis of Gene Expression at the Proteome Level.
- 2.4 Development and Evolution: Comparative Genomics
- 2.5 Functional Genomics/Large-Scale Manipulation of Expression
- 2.6 Computational Approaches
- 3 Model Organisms for Embryogenomics
- 3.1 Non-Mammalian Animals
- 3.2 Mammalian
- 3.3 Plants
- 3.4 Suitability of Approaches for Particular Model Organisms Applied to the Study of Development
- 4 Conclusions
- References
- 4 Interactome
- 1 Introduction
- 2 Experimental Techniques for DetectingProtein Interactions
- 3 Computational Prediction of Protein Interactions
- 3.1 Interaction Prediction from the Gene Patterns Across Genomes
- 3.2 Predicting Interaction from Sequence Coevolution
- 3.3 Domain Interactions
- 3.4 Coexpression Networks
- 4 Exploring the Topology of the Interactome
- 4.1 Global Properties
- 4.2 Network Centrality and Protein Essentiality
- 4.3 Network Modules
- 4.4 Network Motifs and Related Concepts
- 5 Comparing Protein-Protein Interaction Networks
- 6 Databases of Protein and Domain Interactions
- 7 Applications
- 7.1 Predicting Protein Function
- 7.2 Application to Human Diseases
- 8 Looking Ahead: Towards the Dynamic Interactome
- Acknowledgments
- References
- 5 Protein Abundance Variation
- 1 Introduction
- 2 Biochemical Aspects Affecting Protein Abundance in Prokaryotes
- 2.1 Transcription Rate
- 2.2 mRNA Decay
- 2.3 Translation Rate
- 2.4 Protein Stability
- 3 Extracellular Causes Influencing Protein Abundance in Prokaryotes
- 3.1 Nutritional Stress
- 3.2 Thermal Stress
- 3.3 Oxidative Stress
- 4 Biochemical Aspects Affecting Protein Abundance in Eukaryotes
- 4.1 Transcription Rate
- 4.2 Alternative Splicing
- 4.3 mRNA Features Regulating Protein Abundance
- 4.4 mRNA Stability
- 4.5 Translation Rate
- 4.6 Protein Stability
- 5 Other Factors Influencing Protein Abundance in Eukaryotes
- 5.1 Environmental Stress.
- 5.2 Infection
- 5.3 Development
- 6 Techniques Used to Measure Protein Abundance
- 6.1 Correlation between mRNA Abundance and Protein Abundance
- 6.2 Electrophoresis-Based Methods
- 6.3 Quantitative Proteomics
- 6.4 Ribosomal Footprinting
- 6.5 Single-Molecule Real-Time Imaging
- 7 Concluding Remarks and Outlook
- Acknowledgments
- References
- Part II Systems Biology of Evolution
- 6 Genetic Variation and Molecular Darwinism
- 1 Introduction
- 2 Principles of Molecular Evolution
- 2.1 Evolutionary Roles of Genetic Variation, Natural Selection, and Isolation
- 2.2 Molecular Mechanisms of the Generation of Genetic Variation
- 3 Genetic Variation in Bacteria
- 4 Local Changes in the DNA Sequences
- 5 Intragenomic DNA Rearrangements
- 5.1 Site-Specific DNA Inversion at Secondary Crossover Sites
- 5.2 Transposition of Mobile Genetic Elements
- 6 DNA Acquisition
- 7 The Three Natural Strategies Generating Genetic Variations Contribute Differently to the Evolutionary Process
- 8 Evolution Genes and Their Own Second-Order Selection
- 9 Arguments for a General Relevance of the Theory of Molecular Evolution for All Living Organisms
- 10 Systemic Aspects of Biological and Terrestrial Evolution
- 11 Conceptual Aspects of the Theory of Molecular Evolution
- 11.1 Pertinent Scientific Questions
- 11.2 Philosophical Values of the Knowledge on Molecular Evolution
- 11.3 Aspects Relating to Practical Applications of Scientific Knowledge on Molecular Evolution
- References
- 7 Systematics and Evolution
- 1 The Beginning of Molecular Systematics
- 2 The Molecular Assumption
- 3 DNA Hybridization
- 4 Mitochondrial DNA
- 5 DNA Sequences
- 6 Repeated (Retro)Transposons
- 7 ''Evo-Devo''
- 8 Positional Information and Shape
- 9 ''Mutation''
- 10 Toward a Theory of Evolutionary Change.
- 11 Molecules and Systematics: Looking Toward the Future
- References
- 8 Evolution of the Protein Repertoire
- 1 The First Proteins
- 2 Organization of the Modern Protein Repertoire
- 3 Protein Sequence and Its Evolution
- 3.1 Evolution of the Genetic Code
- 3.3 The Organization of Protein Sequences
- 3.4 Genetic Mechanisms of Protein Evolution
- 3.5 Genomic Mechanisms of Protein Evolution
- 4 Protein Structure and Its Evolution
- 4.1 Levels of Protein Structure
- 4.2 Protein Structure In Vivo
- 4.3 Evolution of Protein Structure
- 5 Protein Function and Its Evolution
- 5.1 Types of Protein Function
- 5.2 Functional Networks in Physiology
- 5.3 Evolution of Protein Function
- 6 Protein Evolution in Human Hands
- 6.1 In Vitro Protein Evolution
- 6.2 Computational Protein Evolution
- 7 Lessons from the Evolution of the Protein Repertoire
- References
- Part III Modeling of Biological Systems
- 9 Chaos in Biochemistry and Physiology
- 1 Introduction
- 2 Systems Biology and the Complex Systems Approach: Chaos in Context
- 3 Reconstructing the Underlying Dynamics of Complex Systems
- 4 Chaos, Randomness, and (Colored) Noise
- 5 Nonlinear Time Series Analysis: Conceptual Theoretical and Analytic Tools for Chaos Detection and Characterization
- 6 Periodic and Non-Periodic Dynamics
- 7 Biochemical and Physiological Chaos
- 7.1 Emergent Phenomena in Networks at (Sub) Cellular, Tissue, and Organ Levels
- 7.2 Chaos, Multi-oscillatory Systems, and Inverse Power Laws
- 8 Chaos in Dynamics of Heart and Brain?
- 9 Concluding Remarks: The Status and a Prospective for Chaos
- Acknowledgments
- References
- 10 Computational Biology
- 1 Introduction
- 2 Sequencing Genomes
- 3 Molecular Sequence Analysis
- 3.1 Sequence Alignment
- 3.2 Phylogeny Construction
- 3.3 ''Identifying'' Genes
- 3.4 Analyzing Regulatory Regions.
- 3.5 Finding Repetitive Elements
- 3.6 Analyzing Genome Rearrangements
- 4 Molecular Structure Prediction
- 4.1 Protein Structure Prediction
- 4.2 RNA Secondary Structure
- 5 Analysis of Molecular Interactions
- 5.1 Protein Ligand Docking and Drug Screening
- 5.2 Protein-Protein Docking
- 5.3 Protein Interactions Involving DNA
- 5.4 Protein Design
- 6 Molecular Networks
- 6.1 Different Types of Network
- 6.2 Metabolic Networks
- 6.3 Regulatory and Signaling Networks
- 6.4 Approaches to Analyzing Interaction Networks
- 7 Analysis of Expression Data
- 7.1 Configuration of Experiments and Low-Level Analysis
- 7.2 Classification of Samples
- 7.3 Classification of Probes
- 7.4 Analyzing Transcriptomes with RNA-Seq
- 7.5 Beyond RNA
- 8 Protein Function Prediction
- 8.1 What Is Protein Function?
- 8.2 Function from Sequence
- 8.3 Genomic Context Methods
- 8.4 Function from Structure
- 8.5 Text Mining
- 9 Computational Biology of Diseases
- 9.1 Assessing Disease Risk
- 9.2 Supporting the Prevention of Diseases
- 9.3 Supporting the Diagnosis and Prognosis of Diseases
- 9.4 Supporting the Therapy of Diseases
- 10 Perspectives
- Acknowledgments
- Note on the Second Edition on This Chapter
- References
- 11 Dynamics of Biomolecular Networks
- 1 Introduction
- 2 Boolean Dynamics Models
- 2.1 Boolean Formalisms
- 2.2 Generic Properties of (Random) Boolean Networks and Cell Behaviors: Cell Differentiations and the Cell Cycle
- 2.3 Topological and Dynamical Properties: Homeostasis, Flexibility, and Evolvability
- 2.4 Biologically Relevant Boolean Rules
- 2.5 Dynamical Simulation: An Example
- 2.6 Boolean Networks Inference from Experimental Data: Probabilistic Boolean Networks
- 2.7 Addition of Noise
- 3 Continuous Dynamics Models
- 3.1 ODE Formalisms: From Biochemistry to Mathematics.
- 3.2 Summing Nodes and Links: From Math to Systems Biology.