Biological Circuit Design
Chapters
- 0. Configuring your computer to use Python for scientific computing
 - 1. Introduction to biological circuit design
 - 2. Design principles governing the rate of gene expression
 - 3. Sticky switches: bistability through positive feedback
 - 4. Analysis of feedforward loops
 - 5. Incoherent feed-forward loops serve as dosage compensators
 - 6. Exact adaptation in the chemotaxis pathway
 - 8. Kinetic proofreading: Multi-step processes reduce error rates in molecular recognition
 - 9. Blinking bacteria: The repressilator enables self-sustaining oscillations
 - 10. Uses, simplifications, and elaborations of negative feedback oscillators
 - 11. Time-based regulation in cells
 - 12. Molecular titration generates ultrasensitive responses in biological circuits
 - 13. Promiscuous receptor-ligand interactions increase the bandwidth and specificity of cell-cell communication systems
 - 14. MultiFate enables expandable and controllable multistability
 - 15. The noisy, noisy nature of gene expression: How stochastic fluctuations create variation
 - 16. Bursty gene expression
 - 17. Cellular bet-hedging
 - 18. Excitability enables probabilistic, transient differentiation
 - 20. Lateral Inhibition: Spontaneous symmetry allows spontaneous developmental patterning
 - 21. Turing patterns
 - 22. Scaling reaction-diffusion patterns
 
Technical Appendices
- 2a. Approximate solutions to autorepressive dynamics
 - 2b. Numerical solutions to ODEs with SciPy
 - 2c. Interactive plotting with Bokeh
 - 3a. Nondimensionalization
 - 4a. Numerical solution of FFLs
 - 9a. Fixed points and composite functions
 - 9b. Linear stability analysis
 - 9c. Numerical one-dimensional bounded root finding
 - 10a. Stability diagrams by numerical computation of eigenvalues
 - 10b. The Greshgorin circle theorem
 - 10c. Numerical solution of delay differential equations
 - 10d. Linear stability analysis of delay differential equations
 - 16a. Stochastic (Gillespie) simulation
 - 16b. Profiling code for speed and an application of the Gillespie algorithm
 
Appendices
Package docs