METHODS IN QUANTITATIVE BIOLOGY
Focuses on understanding the key methods and principles of quantitative biology through a close reading of the primary literature. Topics covered will include deterministic and stochastic methods for modeling cellular systems, techniques in systems and synthetic biology, image processing tools and image analysis for biology, data-driven network models, genomic approaches, single-molecule approaches, and key computational biology tools. This course is intended for graduate students from a variety of backgrounds who are interested in pursuing quantitative biology during their graduate studies.
Prerequisites & course information
Requisites: Graduate/professional standing Course Designation: Grad 50% - Counts toward 50% graduate coursework requirement Repeatable for Credit: No Last Taught: Fall 2026 Learning Outcomes: 1. Identify and describe the benefits and limitations of key methods used in the field of quantitative biology Audience: Graduate 2. Critically evaluate experimental and theoretical papers in quantitative biology Audience: Graduate Learning Outcomes: 1. Identify and describe the benefits and limitations of key methods used in the field of quantitative biology Audience: Graduate 2. Critically evaluate experimental and theoretical papers in quantitative biology Audience: Graduate
Sources
- Course catalogue ↗2026-2027