An introduction to dynamical modeling techniques used in contemporary Systems Biology research. We take a case-based approach to teach contemporary mathematical modeling techniques. The course is appropriate for advanced undergraduates and beginning graduate students. Lectures provide biological background and describe the development of both classical mathematical models and more recent representations of biological processes. The course will be useful for students who plan to use experimental techniques as their approach in the laboratory and employ computational modeling as a tool to draw deeper understanding of experiments.

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The course should also be valuable as an introductory overview for students planning to conduct original research in modeling biological systems.

This course focuses on dynamical modeling techniques used in Systems Biology research. These techniques are based on biological mechanisms, and simulations with these models generate predictions that can subsequently be tested experimentally. These testable predictions frequently provide novel insight into biological processes. The approaches taught here can be grouped into the following categories: 1) ordinary differential equation-based models, 2) partial differential equation-based models, and 3) stochastic models.

Course 4 of 6 in the Systems Biology and Biotechnology Specialization.

Syllabus

WEEK 1: Introduction | Computing with MATLAB

WEEK 2: Introduction to Dynamical Systems

WEEK 3: Bistability in Biochemical Signaling Models

WEEK 4: Computational Modeling of the Cell Cycle

WEEK 5: Modeling Electrical Signaling

WEEK 6: Modeling with Partial Differential Equations

WEEK 7: Stochastic Modeling

Systems Biology and Biotechnology Specialization

Computational Modeling