At the graduate level, we are creating new curricula that emphasize the interdisciplinary nature of cellular engineering, while incorporating tools and techniques inspired by Center research. Many of the course topics are grounded in the project arms of the CCC.
Graduate Course Offerings:
Cellular Robotics - Biochem 210/Biophysics 219 (UCSF)
Course Description: In this minicourse, we explore robotics and computer science as paradigms for cellular behavior, in a hands-on project based setting. Students read key literature on cell behavior in which ideas from computer science and electrical engineering are invoked. Then, they are given “challenges” – physical tasks for a robot to solve inspired by some of the things that living cells do, for example multi-cell signaling inspired by Dictyostelium. The students work in small groups to solve these challenges by building and programming robots using the LEGO Mindstorms system. After solving a challenge, students discuss and compare their design solutions, with a particular view to asking whether the robot solved the challenge in a way that resembles how a cell would solve the same problem. Finally, students are asked to redesign their robots using algorithms inspired by cellular signaling pathways. In addition to these bio-inspired challenges, students also explore using Mindstorms to build laboratory automation systems with guest lectures from researchers who have done exactly that.
Systems Biology – Biophysics 205B - (UCSF)
Course Description: The content of this course is directly related to the work of the center. Students are introduced to tools for single cell analysis and multiplexing as they relate to the Center goals of understanding how tissue structure and composition control the flow of information between cells. Additionally, students learn how engineering cell state can affect self-organization of tissues.
Introduction to Cellular Engineering - BIOL/CHEM 877 - (SFSU)
Course Description: This graduate level course takes a quantitative approach to understanding, predicting and engineering cellular behavior. Students learn how to describe complex biological systems with protein, RNA, and DNA components using a mathematical framework. They consider the cell as a compartmentalized reactor with many simultaneously ongoing chemical processes and build models for natural and engineered biological systems. As part of the course, students also design new biological circuits and predict their behavior. The course introduces students to the central engineering ideas that underlie cellular design. Included in the course are discussions of ethical concepts as they relate to Cellular Engineering. For the next iteration of the course, its scope will be broadened. The ultimate goal is for the course to become a permanent addition to the SFSU course catalog, offered annually. This would ensure the course is sustained beyond the life of the STC grant.
Macromolecular Interactions - Biophysics 204B – (UCSF)
Course Description: This new graduate course seeks to achieve a rigorous understanding of the physical principles of macromolecular structure and interactions, and the methods used to define the molecular basis for macromolecular interactions and their function in biology. For example, Sophie Dumont leads a one week-long module in the course that focuses on the mechanics of cellular machines, and how macromolecular machines turn chemical potential into mechanical work. The course contributes to students understanding of the evolution of binding surfaces in cells and is related to the CCC Cellular Machine Shop, CellCAD, and Cellular Legos projects as participants build their understanding of the components for engineering cellular systems.
Tissue Self-Organization – coming Spring 2021
Course Description: This novel course will introduce students to major topics in tissue self-organization through reading of classic papers and manipulation of computational models. As part of this course, students will discuss ethical concepts and responsible innovation in the context of tissue and organ engineering.