Description

Metabolic engineering combines aspects of chemical engineering, systems biology and synthetic biology. This course focuses on developing a quantitative understanding of metabolic processes within the cell. Although metabolism is a complex process, it is determined by a small number of physical constraints, including enzyme activity, mass balance and thermodynamics. In this course you will learn to perform a mass balance, construct and analyze a stoichiometric network, simulate a series of kinetic reactions, and analyze isotope tracer experiments. Key genetic techniques, including CRISPR, will be presented. Computational analysis will be performed using COBRA and Equilibrator via Python and associated tools in the Python Data Science stack. These tools will be applied first to several canonical examples from the metabolic engineering literature and then to a project of your choosing.

Prerequisites

Engineering Sciences 35/160 and a non-introductory course in biochemistry or molecular biology, or permission.