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.
    • Save and load data.
    • 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.