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CHEM_ENG 375: Biochemical Engineering

Modern biochemical engineering. Life sciences microbiology, biochemistry, and modern genetics. Metabolic stoichiometry, energetics, growth kinetics, transport phenomena in bioreactors, and product recovery.

CHEM_ENG 376: Principles in Synthetic Biology

At its core, synthetic biology is inspired by the power and diversity of the living world. It is an endeavor predicated on the idea that we can learn to more reliably and rapidly engineer biological function for compelling applications in medicine, biotechnology, and green chemistry. What is unique to synthetic biology is the application of an engineering-driven approach to accelerate the design-build-test loops required for reprogramming existing, and constructing new, biological systems. In this course the field of synthetic biology and its natural scientific and engineering basis are introduced. 

CHEM_ENG 379: Computational Biology: Principles and Applications

Introduction to the development and application of data-analytical and theoretical methods, mathematical modeling, and computational simulation techniques to the study of biological systems.

CHEM_ENG 395: Global Health and Biotechnology

This class (a) will examine the design, development, and commercialization of healthcare technologies for low-income countries and (b) will explore recent advances in genetic engineering, metabolic engineering, synthetic biology, and tissue engineering. By linking the two, students will gain an understanding of the myriad of commercialization opportunities and challenges associated with deploying these biotechnology advances as healthcare preventative, diagnostic, or treatment products. 

CHEM_ENG 395: Data Analysis and Modeling 

This course introduces machine learning as a tool to select informative and predictive features from “big” and noisy data. Both linear and nonlinear methods of unsupervised and supervised learning are introduced in a project-based setting where students are able to analyze data of interest. Feature selection is coupled with model development to predict non-intuitive responses in test data. Basic coding environments include Matlab, R, and/or Python.

IBiS 455: Current Topics in Synthetic Biology

This course provides an opportunity for in-depth analysis and discussion of select contemporary topics in synthetic biology. The objective of this course is not to provide a comprehensive topical overview, but rather to provide opportunities to think deeply about select topics and to formulate connections between these topics and opportunities for application to ongoing research. The overall format will be that of a comparative journal club presentation and group discussion.

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