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Chapters

0. Configuring your computer to use Python for scientific computing
1. Introduction to biological circuit design
2. Introduction to Python for biological circuits
3. Big functions from small circuits
4. Finding biological circuit motifs
5. Analysis of coherent feed forward loops
6. Incoherent feed-forward loops generate pulses, speed responses, and serve as dosage compensators
7. Molecular titration generates ultrasensitive responses in biological circuits
8. Robustness in biological circuits
9. Kinetic proofreading: Multi-step processes reduce error rates in molecular recognition
10. Blinking bacteria: The repressilator enables self-sustaining oscillations
11. Oscillators, part II: Uses, simplifications, and elaborations of negative feedback oscillators
12. Gene expression is noisy! How stochastic effects lead to heterogeneity
13. Bursty gene expression
14. Stochastic simulation of biological circuits
15. Stochastic differentiation
16. Cellular bet-hedging
17. Time-based regulation in cells
18. Paradoxical regulation in intra- and intercellular circuits
21. Turing patterns
22. Scaling reaction-diffusion patterns
Appendix A: Regulatory functions and their derivatives

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Biological Circuit Design

Last updated on May 26, 2021.

© 2021 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.

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