With the sequencing of the human genome and the genomes of other organisms, we now have a list of the parts that make up these genetic systems. Using this information, researchers are now able to engineer synthetic genetic circuits for a range of applications in the environmental, medical, and energy domains. Crucial to these efforts' success is the development of methods and tools for designing these genetic circuits. While inspiration can be drawn from experiences with electronic design, design with a genetic material poses several challenges. Genetic circuits are composed of very noisy components making their behavior more asynchronous, analog, and stochastic in nature. This specialization presents recent research into new methods and software tools for the modeling, analysis, and design of genetic circuits that are enabling this exciting new field of synthetic biology. As in the sequencing of the human genome, collaborations between engineers and biologists will be essential to the success of synthetic biology. Therefore, the goal of this specialization is to facilitate these collaborations by teaching both the biological and engineering principles necessary for such research.
Overview
Syllabus
Course 1: Engineering Genetic Circuits: Design
- Offered by University of Colorado Boulder. This course gives an introduction to the biology and biochemistry necessary to understand genetic ... Enroll for free.
Course 2: Engineering Genetic Circuits: Modeling and Analysis
- Offered by University of Colorado Boulder. This course gives an introduction to how to create genetic circuit models. These models leverage ... Enroll for free.
Course 3: Engineering Genetic Circuits: Abstraction Methods
- Offered by University of Colorado Boulder. This course introduces how to perform abstraction of genetic circuit models. The first module ... Enroll for free.
- Offered by University of Colorado Boulder. This course gives an introduction to the biology and biochemistry necessary to understand genetic ... Enroll for free.
Course 2: Engineering Genetic Circuits: Modeling and Analysis
- Offered by University of Colorado Boulder. This course gives an introduction to how to create genetic circuit models. These models leverage ... Enroll for free.
Course 3: Engineering Genetic Circuits: Abstraction Methods
- Offered by University of Colorado Boulder. This course introduces how to perform abstraction of genetic circuit models. The first module ... Enroll for free.
Courses
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This course gives an introduction to the biology and biochemistry necessary to understand genetic circuits. It starts by providing an engineering viewpoint on genetic circuit design and a review of cells and their structure. The second module introduces genetic parts and the importance of standards followed by a discussion of genetic devices used within circuit design. The last two modules cover experimental techniques and construction methods and principles applied during the design process.   This course can also be taken for academic credit as ECEA 5934, part of CU Boulder’s Master of Science in Electrical Engineering.
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This course gives an introduction to how to create genetic circuit models. These models leverage chemical reactions represented using the Systems Biology Markup Language (SBML). The second module introduces methods to simulate these models using ordinary differential equation (ODE) methods. The third module teach stochastic simulation methods. The fourth module introduces several variations of the stochastic simulation algorithm. Finally, the fifth module introduces genetic technology method that leverage computational analysis for selecting parts and verifying their performance.   This course can also be taken for academic credit as ECEA 5935, part of CU Boulder’s Master of Science in Electrical Engineering.
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This course introduces how to perform abstraction of genetic circuit models. The first module teaches reaction-based abstraction methods that apply steady-state approximations to reduce the complexity and improve the analysis time of these models. The second module describes piecewise approximations to simplify non-linear reaction-based models of genetic circuits. The third module presents Markov chain models and methods for analyzing them. The fourth module provides methods to abstract models even further using state-based abstraction methods. Finally, the fifth module demonstrates methods, such as infinite-state stochastic model checking, to determine the likelihood that a genetic circuit hazard will cause circuit failure. This course can also be taken for academic credit as ECEA 5935, part of CU Boulder’s Master of Science in Electrical Engineering.
Taught by
Chris Myers and Lukas Buecherl
