Physiological processes can involve a complex level of interactions that can be challenging to understand based on intuition alone. Quantitative and computational approaches can be used to help us better understand the mechanisms regulating such complex processes, both in healthy and pathological conditions. In this course, students will be introduced to current methods from systems biology, computational biology, and artificial intelligence to better understand human physiology. We will discuss mathematical approaches to model biological interactions that describe fundamental physiological concepts such as feedback and homeostasis that operate across biological scales, from intracellular enzymes to organ regulation. We will apply these approaches to understand a range of physiological systems, including hormone secretion, circadian rhythms, and inflammation. We will also introduce students to machine learning and deep learning methods, and discuss how these computational approaches are being applied in the areas of clinical physiology and biomedical imaging.
Gopher Grades is maintained by Social Coding with data from Summer 2017 to Summer 2025 provided by the University in response to a public records request