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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Bibliographic Details
Author / Creator:	Meyers, Robert A.
Format:	eBook Electronic
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.
Subjects:	Systems biology. Biology. Electronic books.
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.

Systems Biology.

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