Epigenetics 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.
1. Section I: Introduction - p. xii 2. Section I. Introduction - p. 1 3. Section II: Where Am I? Genomic Features and DNA Sequence Principles Defining Sites of Epigenetic Regulation: Machine Learning - p. 3 4. Section II. Where Am I? Genomic Features and DNA Sequence Principles Defining Sites of Epigenetic Regulation: Machine Learning - p. 5 5. Chapter 1. Computational Identification of Polycomb/Trithorax Response Elements - p. 7 6. Chapter 2. Modeling Chromatin States - p. 25 7. Chapter 3. Crossing Borders: Modeling Approaches to Understand Chromatin Domains and Their Boundaries - p. 45 8. Chapter 4. Inferring Chromatin Signaling From Genome-Wide ChIP-seq Data - p. 69 9. Section III: Everything’s Moving: In Vivo Dynamics of Epigenetic Regulators: Kinetic Models Based on Ordinary Differential Equations - p. 85 10. Section III. Everything’s Moving: In Vivo Dynamics of Epigenetic Regulators: Kinetic Models Based on Ordinary Differential Equations - p. 87 11. Chapter 5. “In Vivo Biochemistry”: Absolute Quantification and Kinetic Modeling Applied to Polycomb and Trithorax Regulation - p. 89 12. Chapter 6. Modeling Distributive Histone Modification by Dot1 Methyltransferases: From Mechanism to Biological Insights - p. 117 13. Section IV: Reconciling Randomness and Precision: Bistable Epigenetic Memory and Switching: Stochastic Models - p. 141 14. Section IV. Reconciling Randomness and Precision: Bistable Epigenetic Memory and Switching: Stochastic Models - p. 143 15. Chapter 7. Modeling Bistable Chromatin States - p. 145 16. Chapter 8. Quantitative Environmentally Triggered Switching Between Stable Epigenetic States - p. 169 17. Section V: The Third and Fourth Dimensions: Chromosomal Long Range Interactions: Polymer Models - p. 187 18. Section V. The Third and Fourth Dimensions: Chromosomal Long Range Interactions: Polymer Models - p. 189 19. Chapter 9. On the Nature of Chromatin 3D Organization: Lessons From Modeling - p. 191 20. Chapter 10. From Chromosome Conformation Capture to Polymer Physics and Back: Investigating the Three-Dimensional Structure of Chromatin Within Topological Associating Domains - p. 203 21. Chapter 11. A Combination Approach Based on Live-Cell Imaging and Computational Modeling to Further Our Understanding of Chromatin, Epigenetics, and the Genome - p. 225 22. Chapter 12. Capturing Chromosome Structural Properties From Their Spatial and Temporal Fluctuations - p. 239 23. Index - p. 265
Epigenetics 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.
1. Section I: Introduction - p. xii 2. Section I. Introduction - p. 1 3. Section II: Where Am I? Genomic Features and DNA Sequence Principles Defining Sites of Epigenetic Regulation: Machine Learning - p. 3 4. Section II. Where Am I? Genomic Features and DNA Sequence Principles Defining Sites of Epigenetic Regulation: Machine Learning - p. 5 5. Chapter 1. Computational Identification of Polycomb/Trithorax Response Elements - p. 7 6. Chapter 2. Modeling Chromatin States - p. 25 7. Chapter 3. Crossing Borders: Modeling Approaches to Understand Chromatin Domains and Their Boundaries - p. 45 8. Chapter 4. Inferring Chromatin Signaling From Genome-Wide ChIP-seq Data - p. 69 9. Section III: Everything’s Moving: In Vivo Dynamics of Epigenetic Regulators: Kinetic Models Based on Ordinary Differential Equations - p. 85 10. Section III. Everything’s Moving: In Vivo Dynamics of Epigenetic Regulators: Kinetic Models Based on Ordinary Differential Equations - p. 87 11. Chapter 5. “In Vivo Biochemistry”: Absolute Quantification and Kinetic Modeling Applied to Polycomb and Trithorax Regulation - p. 89 12. Chapter 6. Modeling Distributive Histone Modification by Dot1 Methyltransferases: From Mechanism to Biological Insights - p. 117 13. Section IV: Reconciling Randomness and Precision: Bistable Epigenetic Memory and Switching: Stochastic Models - p. 141 14. Section IV. Reconciling Randomness and Precision: Bistable Epigenetic Memory and Switching: Stochastic Models - p. 143 15. Chapter 7. Modeling Bistable Chromatin States - p. 145 16. Chapter 8. Quantitative Environmentally Triggered Switching Between Stable Epigenetic States - p. 169 17. Section V: The Third and Fourth Dimensions: Chromosomal Long Range Interactions: Polymer Models - p. 187 18. Section V. The Third and Fourth Dimensions: Chromosomal Long Range Interactions: Polymer Models - p. 189 19. Chapter 9. On the Nature of Chromatin 3D Organization: Lessons From Modeling - p. 191 20. Chapter 10. From Chromosome Conformation Capture to Polymer Physics and Back: Investigating the Three-Dimensional Structure of Chromatin Within Topological Associating Domains - p. 203 21. Chapter 11. A Combination Approach Based on Live-Cell Imaging and Computational Modeling to Further Our Understanding of Chromatin, Epigenetics, and the Genome - p. 225 22. Chapter 12. Capturing Chromosome Structural Properties From Their Spatial and Temporal Fluctuations - p. 239 23. Index - p. 265
