Biochem 210 Systems Biology: Cellular Robotics (2017)

Module: 2
Sponsoring Program: Tetrad
Administrator: Toni Hurley

Course Number: Biochem 210/BP 219
Course Name: Systems Biology: Cellular Robotics
Units: 3
Grading Option: S/U
Course Director: Jennifer Fung

Additional Course Director(s): Wallace Marshall
Room Number: QB3 Teaching Lab, GH-227
Campus: Mission Bay
Schedule: April 24 - May 12, 2017; 10:00 AM - 12:00 PM
Prerequisites: None
Maximum Class Size: 10-12

Course Description: Cells are complex biological machines, capable of making decisions and performing behaviors both individually and in groups.   Much of physiology and development hinges on cells executing the correct behaviors at the appropriate times, in response to sensory inputs from their environment.  In this respect, cells resemble man-made robots.  By viewing cells as robots, controlled by computational circuitry made of genes and signaling molecules, it is possible to apply concepts from engineering and computer science to understand cellular behavior.  In order to exploit such concepts, it is important to have a firm foundation in how robots are actually built and programmed.  In our minicourse, we will explore robotics and computer science as paradigms for cellular behavior, in a hands-on project based setting.  Students will read key literature on cell behavior in which ideas from computer science and electrical engineering are invoked. Then, they will be given “challenges” – physical tasks for a robot to solve inspired by some of the things that living cells do.  The students will work in small groups to solve these challenges by building robots using the LEGO Mindstorms system – a robotics platform largely intended for children but which is in fact built on a powerful LabView software system and which allows concepts such as path planning and feedback to be rapidly prototyped.  After solving a challenge, students will discuss and compare their designs, 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, they will be asked to redesign their robots using algorithms inspired by cellular signaling pathways.  In addition to these bio-inspired challenges, students will also explore using Mindstorms to building laboratory automation systems with guest lectures from researchers who have done exactly that.   We imagine three key learning outcomes from the course:  (1) Learn how to apply central topics in robotics and programming hands-on in the real world, not just in theory.  Examples include proportional control, fine state automata models, multithreaded programming, and servomotor systems.  Design and debugging will be emphasized in this objective.  (2) How to think about the applicability (or not) of engineering concepts for biological systems.  (3)  View the cell as a system that can be programmed and re-engineered.