Modeling Biological Dynamics (338-0-1)
Instructors
Rosemary I Braun
Meeting Info
2122 Sheridan Rd Classroom 250: Tues, Thurs 3:30PM - 4:50PM
Overview of class
Life is an inherently dynamic process, and the dynamics at every scale of organization -- from the atomic self-assembly of macromolecular complexes to the interactions of species in an ecology -- can give rise to surprising outcomes. Predicting and modulating those dynamics requires the development of accurate mathematical and computational models. In this class, you will learn about mathematical and computational techniques for analyzing and predicting biological dynamics. Techniques will include statistical models, discrete- and continuous- time dynamical models, and stochastic models. Applications will cover a range of scales, from biomolecules to population dynamics, with an emphasis on common mathematical concepts and computational techniques, the interpretation of existing data, and making predictions for new experiments.
Registration Requirements
An introductory course in calculus, statistics, or linear algebra (at least one of MATH 218/220, MATH 240, STAT 202, or BIOL_SCI 337, or the equivalent), or permission of instructor. No prior programming knowledge is assumed, although it will be helpful. Curiosity and fearlessness are required.
Teaching Method
Evaluation Method: Quizzes (10%), Homework (40%), Participation (20%), Project & Presentation (30%)
Class Materials (Required)
• Alan Garfinkel, Jane Shevtsov, and Yina Guo. Modeling Life. Springer (2017). ISBN: 978-3-319-59731-7 Free (if using NU wifi or VPN): Free: https://link.springer.com/content/pdf/10.1007%2F978-3-319-59731-7.pdf
• SageMath software (including Python):
Free: https://www.sagemath.org
Class Materials (Suggested)
• Philip Nelson. Physical Models of Living Systems, 2nd Ed. Chiliagon (2021).
$10: Kindle Edition
• Stephen P. Ellner and John Guckenheimer. Dynamic Models in Biology. Princeton (2006).
Class Attributes
Formal Studies Distro Area
Enrollment Requirements
Enrollment Requirements: Prerequisites: at least one of MATH 218-1, MATH 220-1, MATH 240-0, STAT 202-0, BIOL_SCI 337-0, OR equivalent.