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Epigenetics and Systems Biology
- 1st Edition - April 25, 2017
- Author: Leonie Ringrose
- Language: English
- Hardback ISBN:9 7 8 - 0 - 1 2 - 8 0 3 0 7 5 - 2
- eBook ISBN:9 7 8 - 0 - 1 2 - 8 0 3 0 7 6 - 9
Epigenetics and Systems Biology highlights the need for collaboration between experiments and theoretical modeling that is required for successful application of systems biology i… Read more
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Request a sales quoteEpigenetics and Systems Biology highlights the need for collaboration between experiments and theoretical modeling that is required for successful application of systems biology in epigenetics studies.
This book breaks down the obstacles which exist between systems biology and epigenetics researchers due to information barriers and segmented research, giving real-life examples of successful combinations of systems biology and epigenetics experiments.
Each section covers one type of modeling and one set of epigenetic questions on which said models have been successfully applied. In addition, the book highlights how modeling and systems biology relate to studies of RNA, DNA, and genome instability, mechanisms of DNA damage signaling and repair, and the effect of the environment on genome stability.
- Presents original research in a wider perspective to reveal potential for synergies between the two fields of study
- Provides the latest experiments in primary literature for the modeling audience
- Includes chapters written by experts in systems biology and epigenetics who have vast experience studying clinical applications
Researchers in epigenetics, genetics, systems biology, and computational biology with a background in molecular biology, genetics
Section I: Introduction
- References
Section II: Where Am I? Genomic Features and DNA Sequence Principles Defining Sites of Epigenetic Regulation: Machine Learning
Chapter 1. Computational Identification of Polycomb/Trithorax Response Elements
- Abstract
- Introduction to Polycomb/Trithorax Response Elements
- 2003 Ad Hoc Approach to PRE Prediction, Together with its Particular Motivations
- Evaluating Classification Performance
- Results of 2003 PRE Prediction
- New Motifs Discovered
- Recasting PRE Prediction as a Machine Learning Problem
- Misclassification Costs and the Trade-off Dimension
- Evolutionary Analysis and Search-Space Reduction
- Today: Genome-Wide Profiling Data
- How Good is Our Method When Evaluated Under These Data?
- Sensitivity and Specificity of Genome-Wide Profiling
- Conclusion
- References
- Glossary
- List of Acronyms and Abbreviations
Chapter 2. Modeling Chromatin States
- Abstract
- The Purpose of Modeling Chromatin States
- The Common Approach
- What Have We Learned From those Models?
- Static Versus Dynamical Models
- Chromatin States are Attractors
- References
- Glossary
- List of Acronyms and Abbreviations
Chapter 3. Crossing Borders: Modeling Approaches to Understand Chromatin Domains and Their Boundaries
- Abstract
- Introduction
- The Expanding Universe of Structural Domains
- Experimental Techniques
- Modeling Higher Order Chromatin Structure
- Formalizing Compartment Calling and Boundary Prediction
- Outlook
- References
- List of Acronyms and Abbreviations
Chapter 4. Inferring Chromatin Signaling From Genome-Wide ChIP-seq Data
- Abstract
- Introduction
- Experimental Techniques
- Modeling
- Perturbing the System
- Outlook
- References
- Glossary
- List of Acronyms and Abbreviations
Section III: Everything’s Moving: In Vivo Dynamics of Epigenetic Regulators: Kinetic Models Based on Ordinary Differential Equations
Chapter 5. “In Vivo Biochemistry”: Absolute Quantification and Kinetic Modeling Applied to Polycomb and Trithorax Regulation
- Abstract
- Introduction
- Absolute Quantification In Vivo: A Technical Challenge
- Everything’s Moving: Methods for Measuring Kinetic Parameters In Vivo
- In Vivo Biochemistry of an Epigenetic System: What Did We Learn?
- Mathematical Modeling of the System: Defining What We Don’t Know
- Back to the Bench: Testing the Model by Perturbing the System
- Outlook
- Acknowledgments
- References
- Glossary
- List of Acronyms and Abbreviations
Chapter 6. Modeling Distributive Histone Modification by Dot1 Methyltransferases: From Mechanism to Biological Insights
- Abstract
- Introduction
- Modeling Histone Modification by Dot1
- Acknowledgments
- References
- Glossary
- List of Acronyms and Abbreviations
- Appendix: Parameter Estimation and Formal Mathematical Description of the Models
Section IV: Reconciling Randomness and Precision: Bistable Epigenetic Memory and Switching: Stochastic Models
Chapter 7. Modeling Bistable Chromatin States
- Abstract
- Cell Memory by Chromatin-Based Epigenetics
- Modeling Approach and Philosophy
- Nucleosome-Mediated Epigenetics
- DNA Methylation-Mediated Epigenetics
- Outlook
- References
- Glossary
- List of Acronyms and Abbreviations
Chapter 8. Quantitative Environmentally Triggered Switching Between Stable Epigenetic States
- Abstract
- Introduction
- Memory of the Cold is Digital and is Stored Locally in the Chromatin
- Cold Registration is Digital
- Model Validation
- Outlook
- References
- Glossary
- List of Acronyms and Abbreviations
Section V: The Third and Fourth Dimensions: Chromosomal Long Range Interactions: Polymer Models
Chapter 9. On the Nature of Chromatin 3D Organization: Lessons From Modeling
- Abstract
- Introduction
- Polymer Models of Chromatin
- Models to Reconstruct 3D-Conformation From Contact Data
- Conclusions
- References
- Glossary
Chapter 10. From Chromosome Conformation Capture to Polymer Physics and Back: Investigating the Three-Dimensional Structure of Chromatin Within Topological Associating Domains
- Abstract
- Introduction
- From 5C/Hi-C Maps to Three-Dimensional Structures
- Description of the Data-Driven Polymer Model
- What can be Learned From Data-Driven, Polymer-Based Reconstructions of Chromosome Structure?
- What are the Molecular Mechanisms Behind Interaction Energies?
- Conclusions and Perspectives
- References
- Glossary
- List of Acronyms and Abbreviations
Chapter 11. A Combination Approach Based on Live-Cell Imaging and Computational Modeling to Further Our Understanding of Chromatin, Epigenetics, and the Genome
- Abstract
- Introduction: Genomic DNA, Nucleosomes, and Chromatin
- Experimental Techniques: Single-Nucleosome Imaging in Living Cells Using Super-Resolution Microscopy
- Modeling: Monte Carlo Simulation of Chromatin Dynamics
- Another Result From the Model: Physical Size of Transcription Complexes
- Perspective
- References
- Glossary
- List of Acronyms and Abbreviations
Chapter 12. Capturing Chromosome Structural Properties From Their Spatial and Temporal Fluctuations
- Abstract
- Introduction
- Chromosome Labeling Technologies
- Spatial Dynamics: Real-Time Imaging and Tracking of Single Chromosome Loci
- Mapping Chromosome Conformational Dynamics by Single/Multi Loci Positioning
- Outlook—Future Developments
- References
- Glossary
- No. of pages: 286
- Language: English
- Edition: 1
- Published: April 25, 2017
- Imprint: Academic Press
- Hardback ISBN: 9780128030752
- eBook ISBN: 9780128030769
LR
Leonie Ringrose
Leonie Ringrose is Professor of Quantitative Biology at the Integrated Research Institute for Lifesciences and Humboldt University Berlin, Germany. Her laboratory studies quantitative epigenetics
Affiliations and expertise
Professor at the IRI Lifesciences, Humboldt University, BerlinRead Epigenetics and Systems Biology on ScienceDirect