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.
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Engineering Genetic Circuits: Abstraction Methods
This course is part of Engineering Genetic Circuits Specialization
Recommended experience
What you'll learn
Derive abstracted reaction-based models of genetic circuits.
Utilize piecewise models of genetic circuits.
Perform analysis of Markov chain models.
Construct state-based abstracted models of genetic circuits.
Skills you'll gain
Details to know
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July 2024
12 assignments
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There are 5 modules in this course
This module will introduce methods to simplify chemical reaction models using automated model abstraction techniques.
What's included
13 videos3 readings2 assignments1 peer review
This module will introduce methods for abstracting models using piecewise linear representations.
What's included
12 videos3 readings3 assignments
This module will introduce Markov chains and analysis methods for them.
What's included
12 videos3 readings3 assignments
This module will introduce a state-based abstraction workflow and analysis methods for these abstracted models.
What's included
8 videos3 readings3 assignments
This module introduces genetic circuit hazards and how to determine the likelihood that they cause circuit failure.
What's included
10 videos3 readings1 assignment2 peer reviews
Instructors
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Recommended if you're interested in Electrical Engineering
Google Cloud
University of Colorado Boulder
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