This course seeks to build the student‘s strength in Chemical Engineering computing and data analysis. The first part of the course develops programming skills and numerical methods in Matlab (Octave) that will be useful for solving problems related to Process Analysis, Thermodynamics, Transport Phenomena, and Kinetics. In the second part of the course, we will learn mathematical methods related to statistical analysis and hypothesis testing.
This course covers new topics in the design of systems of biomolecules, both in vitro and in vivo, for decision making and control. The course will begin with an overview of how logical decision making and control with biomolecules as is achieved in biology and then proceed to consider various strategies of engineering similar systems. The focus of the course will be on systems level principles rather than the biochemistry of molecule design. Topics will include engineering of transcriptional networks and genetic control for logical programming of cells, the design of in vitro mimics of genetic controls, molecular computing and systems aspects of metabolic engineering. The course will also cover quantitative and computational techniques for the simulation and analysis of biomolecular systems.
From the smallest change in gene expression to life and death and reproduction, biomolecular decision-making processes govern cellular fate. In this course we explore the design principles by which biomolecules make decisions and orchestrate complex processes such as signal transduction, homeostasis or apoptosis. We will also explore how we can in turn design complex biomolecular networks that can control biological systems and biomolecular materials. Topics will include the design and analysis of molecular logic circuits, transcriptional and translational control, signal transduction cascades, biomolecular oscillators and cycles, DNA nanotechnology and nanobiotechnology, and molecular computing. The course will introduce principles from electrical circuit theory, computing and control theory and show how these tools can be applied to these systems. Students should be familiar with programming and chemical engineering principles.