Course Description

Life is sustained by constant change: molecules react, genes are expressed, populations evolve. These dynamic regimes are best represented by mathematical models that explicitly describe these processes.

This seven-week course introduces mathematical modeling of biological systems with an emphasis on dynamic models. To that end, an introduction and refresher of calculus -- the mathematics of change -- is done in the context of classic models like enzyme (Michaelis–Menten) kinetics, Predator-Prey (Lotka-Volterra) equations, and epidemic (Ross-McDonald) models. Modern applications of dynamic models and their combination with data through state-of-the-art statistical inference are then presented with an overview of the challenges and perspectives in a broad context of real-world research.

Learner Outcomes

• Describe natural processes as explicit mathematical functions
• Formulate models in the absence of complete mathematical knowledge by implicitly describing known interactions
• Modify the output of model solution or simulation by changing variables (parameters)
• Describe the reverse process of inferring parameters from data

Credentials

This course applies toward the Bioinformatics Curiosity digital badge

Textbook Information

Textbook Recommended:

Biocalculus: Calculus, Probability, and Statistics for the Life Sciences (1st Edition, 2014/2015) by James Stewart and Troy Day
ISBN: 9781305114036 |  $274.95

Note: Please remove the textbook at checkout using the appropriate discounts if you do not wish to purchase it.