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Computational Systems Biology
From Molecular Mechanisms to Disease
2nd Edition - November 26, 2013
Editors: Andres Kriete, Roland Eils
Language: English
Hardback ISBN:9780124059269
9 7 8 - 0 - 1 2 - 4 0 5 9 2 6 - 9
eBook ISBN:9780124059382
9 7 8 - 0 - 1 2 - 4 0 5 9 3 8 - 2
This comprehensively revised second edition of Computational Systems Biology discusses the experimental and theoretical foundations of the function of biological systems at the mo…Read more
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This comprehensively revised second edition of Computational Systems Biology discusses the experimental and theoretical foundations of the function of biological systems at the molecular, cellular or organismal level over temporal and spatial scales, as systems biology advances to provide clinical solutions to complex medical problems. In particular the work focuses on the engineering of biological systems and network modeling.
Logical information flow aids understanding of basic building blocks of life through disease phenotypes
Evolved principles gives insight into underlying organizational principles of biological organizations, and systems processes, governing functions such as adaptation or response patterns
Coverage of technical tools and systems helps researchers to understand and resolve specific systems biology problems using advanced computation
Multi-scale modeling on disparate scales aids researchers understanding of dependencies and constraints of spatio-temporal relationships fundamental to biological organization and function.
Graduate students and researchers in Bioinformatics, Biocomputing, Theoretical Biology, Biochemistry/Biophysics, and Cell Biology.
Preface
Chapter 1. Introducing Computational Systems Biology
1 Prologue
2 Overview of the content
3 Outlook
References
Chapter 2. Structural Systems Biology: Modeling Interactions and Networks for Systems Studies
Abstract
Acknowledgments
1 Introduction
2 A brief history of structural bioinformatics
3 Structural analysis of interaction data
4 Other interaction types
5 Systems biology applications
6 New datasets-specific protein sites
7 Current and future needs
8 Concluding remarks
References
Chapter 3. Understanding Principles of the Dynamic Biochemical Networks of Life Through Systems Biology
Abstract
Acknowledgments
1 Principles based on topology of the genome-wide metabolic network: limited numbers of possible flux patterns
2 Principles based on topology of the genome-wide metabolic network: toward personalized medicine
3 Industrially relevant applications of topology and objective-based modeling
4 Applications of topology and objective-based modeling to cancer research and drug discovery
5 Principles of control
6 Principles of regulation
7 Regulation versus control
8 Robustness and fragility and application to the cell cycle
9 Perfect adaptation and integral control in metabolism
References
Chapter 4. Biological Foundations of Signal Transduction, Systems Biology and Aberrations in Disease
Abstract
1 Introduction
2 Concepts in signal transduction
3 Mathematical modeling of signaling pathways
4 Conclusion
References
Chapter 5. Complexities in Quantitative Systems Analysis of Signaling Networks
Abstract
1 Introduction
2 Requirements for a quantitative systems analysis of signaling networks
3 Synthetic biology approaches in signal transduction
4 Outlook
References
Chapter 6. Gene Networks: Estimation, Modeling, and Simulation
Abstract
Acknowledgments
1 Introduction
2 Gene network estimation from microarray gene expression data
3 Advanced methods for gene network estimation
4 Petri net based modeling of gene networks
5 Conclusion
6 Related internet resources
References
Chapter 7. Reconstruction of Metabolic Network from Genome Information and its Structural and Functional Analysis
Abstract
1 Introduction
2 Reconstruction of genome scale metabolic networks
3 Mathematical representation of metabolic networks
4 Structural analysis of metabolic networks
5 From network to modules
6 Concluding remark
References
Chapter 8. Standards, Platforms, and Applications
Abstract
Acknowledgments
1 Introduction
2 Standards
3 Future considerations
4 Platforms
5 Applications
6 Future prospects and conclusion
7 Recommended resources
References
Chapter 9. Databases, Standards, and Modeling Platforms for Systems Biology
Abstract
1 Introduction
2 Pathway Databases
3 Model Databases
4 Systems Biology Standards
5 Simulation and Modeling Platforms
6 Conclusion
7 Outlook
References
Chapter 10. Computational Models for Circadian Rhythms: Deterministic versus Stochastic Approaches
Abstract
Acknowledgments
1 Introduction: the computational biology of circadian rhythms
2 Modeling the Drosophila circadian clock
3 Stochastic models for circadian rhythms
4 Modeling the mammalian circadian clock
5 Conclusions
References
Chapter 11. Top-Down Dynamical Modeling of Molecular Regulatory Networks
Abstract
Acknowledgments
1 Introduction
2 Top-down modeling
3 Discrete models
4 Discrete methods for top-down modeling
5 Data discretization
6 Relationship between discrete and continuous top-down modeling
7 Toward a mathematical theory of biological system identification
8 Conclusion
References
Chapter 12. Discrete Gene Network Models for Understanding Multicellularity and Cell Reprogramming: From Network Structure to Attractor Landscapes Landscape
Abstract
1 Introduction
2 GENE regulatory networks and cell types: attractors in a dynamical system
3 BOOLEAN networks for multicellularity
4 Dynamics of Large Ensemble of Networks
5 Development of multicellularity: relative stability of states and global ordering
6 BOOLEAN network model of neuron cell differentiation and reprogramming
7 BOOLEAN network model for pancreas development and reprogramming
8 Conclusion—toward a la carte cell reprogramming
References
Chapter 13. Stochastic Simulations of Cellular Processes: From Single Cells to Colonies
Abstract
Acknowledgments
1 Introduction
2 CME and RDME simulations in Lattice Microbes
3 Simulating the lac genetic Switch in E. coli
4 Simulating MinDE oscillations in E. coli
5 Hybrid RDME/FBA simulations of a bacterial colony
References
Chapter 14. Advances in Machine Learning for Processing and Comparison of Metagenomic Data
Abstract
Acknowledgments
1 Introduction
2 Preprocessing
3 Annotation of genes
4 Cross sample analysis
5 Understanding Microbial Communities
6 Open Problems and Challenges
References
Chapter 15. Systems Biology of Infectious Diseases and Vaccines
1 Introduction
2 A brief overview of the immune response
3 Systems immunology tools and databases
4 Blood transcriptomics
5 Systems biology of infectious diseases
6 Systems vaccinology
7 Challenges and limitations
8 Conclusions
References
Chapter 16. Computational Modeling and Simulation of Animal Early Embryogenesis with the MecaGen Platform
Abstract
1 Introduction
2 MECA: model of cell biomechanics
3 GEN: model of genetic regulation and molecular signaling
4 MECAGEN: model of mechanic-genetic coupling
5 Illustrations on artificial data
6 Biological case study: intercalation patterns in the zebrafish epiboly
7 Discussion
References
Chapter 17. Developing a Systems Biology of Aging
Abstract
1 Introduction
2 Aging networks
3 Regulatory control mechanisms in aging
4 Cell models of parkinson’s disease
5 Simulations and predictions
6 Robustness in the context of theories and models of aging
7 Discussion and outlook
References
Chapter 18. Molecular Correlates of Morphometric Subtypes in Glioblastoma Multiforme
Abstract
1 Introduction
2 Background
3 Morphometric representation
4 Bioinformatics analysis
5 Computational pipeline
6 Conclusion
References
Chapter 19. Applications in Cancer Research: Mathematical Models of Apoptosis
Abstract
1 The perspective of apoptosis models in cancer research
Associate Professor for Bioinformation Engineering at Drexel University, Philadelphia and Director of the Biocomputing Laboratory at the Coriell Institute for Medical Research
Affiliations and expertise
Drexel University, Philadelphia, PA and Coriell Institute for Medical Research, Camden, NJ, USA
RE
Roland Eils
Professor of Bioinformatics at the University of Heidelberg and Director of the Division of Theoretical Bioinformatics at the German Cancer Research Center (DKFZ) in Heidelberg
Affiliations and expertise
Theoretical Bioinformatics, German Cancer Research Center (DKFZ), Heidelberg, and Bioinformatics and Functional Genomics, Institute of Pharmacy and Molecular Biotechnology, University of Heidelberg, Germany