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


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.


Previous knowledge (preferably a full-semester course) of calculus is strongly recommended, but not required -- solid understanding of functions of the form y=f(x) and their 2D graphing is required. If you are unsure that you meet the prerequisite requirements, please contact registrar@faes.org and provide information about your course of interest and background knowledge.

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