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Revision as of 23:13, 28 September 2011
Introduction to Synthetic Biology : Fall 2011
- BioE 423/523, CSE 486/586, EE 423/523
- Instructor: Prof. Eric Klavins
- Office Hours: Tu, Th 9:00AM - 10:20AM, CSE 236
- Teaching Assistant: Shelly Jang
- Office Hours: Mo, Fr, 10:00AM - 11:20, EEB M406
- MWF 11:30-12:20
- MOR 234
|1||9/28||Introduction||Special Issue of Science on Synthetic Biology: Read the introduction, news, reviews and perspectives sections. Optionally, check out various other reviews.||A1, due 10/5||-|
|9/30||Growth||Various Optional Reading on Growth.||-||-|
The following topics will be covered in this course, approximately in the order listed.
- Growth and cell division, mainly in bacteria. Dilution due to cell growth. Sources of noise. Sizes and numbers in cells.
- Gene expression and regulation. Bacterial promoters and ribosome binding sites. Inducers.
- Stohasticity. Intrinsic and extrinsic noise. Basics of probabilistic modeling. Negative feedback reduces noise. Noise in nature: bet-hedging, coin-flipping, symmetry breaking.
- State. The genetic toggle switch. Positive feedback. Distributed algorithms in bacterial micro-colonies. Leader election and symmetry breaking. Synthetic development and morphogenesis.
- Signalling. Two component systems, MAPK, quorum sensing, auxin signalling. Boolean logic, transfer functions, etc. implemented in cells.
- Dynamics. Synthetic oscillators: The repressilator. Synchronized oscillators. Other dynamic behaviors. Modeling and analysis of dynamic systems.
- Tuning. Sensitivity analysis. Fine tuning behaviors via promotors, ribosome binding sites, protein and RNA degradation rates. Recombineering and MAGE.
- Evolution. Basics of creating variation and selection. Mutation rates and DNA repair. Continuous culture devices. Examples of directed evolution.
In addition, the following topics will be interspersed as needed.
- Applications. Therapeutics, diagnostics, biofuels, bio-remediation, global health.
- Modeling. Deterministic, stochastic, black-box.
- Software. Various tools for modeling and designing synthetic biological systems.
- Data and parameter estimation.
- Construction. Gene synthesis, assembly, and verification. Plasmids, integrations, etc.
- Assays. Microscopy, cytometry, micro-fluidics, sequencing, plate-readers, etc.