# Computer Lab (Biological Modeling: Mathematical and Computational Approaches)

Teaching Assistant (C&SB 150), UCLA, Computational and Systems Biology, 2019

Lead the computer labs where we explore various biological modeling through computational approach (Matlab), e.g. Lokta-Volterra model, Michaelis Menten Model, Hodgkin-Huxley Model, SIR model, Network, Fractal and etc…

Here is the syllabus for the course.

# List of labs with description:

• Week1: Intro to Matlab & ODE Solving
• What is Matlab?
• Basic operations and coding.
• Writing scripts and functions.
• Loops.
• Boolean.
• Vectorize.
• ODE45.
• Examine different types of numerical solvers for ODE and the effect of step size on the error.
• Week2: Eigenvalues
• Brief explanation of how to find eigenvalues.
• Logic of basic methods and characteristic equations and polynomial.
• Week3: Bistability
• Use Matlab to simulate and analyze dynamical systems that use ODE; use ODE45 to numerically solve; address fixed points and nullclines; also perform sensitivity analysis.
• Week4: Predator-Prey
• Develop agent-based model for predator-prey dynamics; study how “handling time” arise from individual dynamics.
• Week5: Epidemic outbreaks
• Model outbreaks using SIR/SIRS model; study the speed, strength and size of outbreaks.
• Week6: Michaelis Menten
• Michaelis-Menten enzyme-substrate dynamics and the Quasi Steady State Assumption.
• Week7: Hodgkin-Huxley
• Use Matlab to simulate an excitatory system with the specific case-study of a neuron in mind.
• Week8: Network
• Use Gephi to study some properties of various networks and methods of how to visualize them.
• Week9: Fractal
• Learn basic skills you need for analyzing fractals, including box counting method, manipulating images, thresholding, and a bit about regression and model comparison.
• Week10: Game Theory
• Explore the interactions between strategies, games, and population outcomes.