Logo

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

  • Appendix A: Mathematical review
  • Appendix B: Introduction to Python
  • Appendix C: Numerical solutions of ODES
  • Appendix D: Regulatory functions and their derivatives

Package docs

  • biocircuits package documentation
Biological Circuit Design
  • Search


Last updated on Mar 23, 2025.

© 2021–2025 Michael Elowitz and Justin Bois. With the exception of pasted graphics, where the source is noted, this work is licensed under a Creative Commons Attribution License CC BY-NC-SA 4.0. All code contained herein is licensed under an MIT license.

This document was prepared at Caltech with financial support from the Donna and Benjamin M. Rosen Bioengineering Center.



Built with Sphinx using a theme provided by Read the Docs.