# Biological Circuit Design¶

This course focuses on quantitative studies of cellular and developmental systems in biology, including the architecture of specific genetic circuits controlling microbial behaviors and multicellular development in model organisms. Topics are approached from experimental, theoretical and computational perspectives. Our goals for the class are (a) to build understanding of key principles of systems biology and (b) to develop skills for modeling and analysis of genetic circuits.

## People¶

Instructors

Justin Bois (bois at caltech dot edu)

Michael Elowitz (melowitz at caltech dot edu)

TAs

John Marken (jmarken at caltech dot edu)

Ankita Roychoudhury (aroychou at caltech dot edu)

- 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