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Computational Systems Biology
 
 

Computational Systems Biology, 2nd Edition

From Molecular Mechanisms to Disease

 
Computational Systems Biology, 2nd Edition,Andres Kriete,Roland Eils,ISBN9780124059269
 
 
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Kriete   &   Eils   

Academic Press

9780124059269

9780124059382

548

235 X 191

This comprehensively revised new edition reviews fundamentals and recent breakthroughs in computational simulation and multi-scale analysis techniques across biological systems, with new chapters covering complex systems and emerging phenotypes.

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Key Features

  • 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.

Description

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.

Readership

Graduate students and researchers in Bioinformatics, Biocomputing, Theoretical Biology, Biochemistry/Biophysics, and Cell Biology.

Andres Kriete

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

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

Computational Systems Biology, 2nd Edition

  • 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
    • 2 Overview of mathematical formalisms
    • 3 Mechanistic ODE models describing apoptosis networks
    • 4 Conclusions
    • References
  • Author Index
  • Subject Index

Quotes and reviews

"…revised and updated to include the latest advances in cancer, aging, and development modeling research. The first chapter introduces the field and reviews the content to follow, while the ensuing six chapters lay the foundations of modeling networks, systems analysis, biochemistry, and signal transduction underlying the systems approach,…"--ProtoView.com, April 2014

 
 
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