CSE P 590, Winter 2014

Prof. Georg Seelig

PAC 228, Office Hours by Appointment (send email w/schedule, or stop by)


Kevin Oishi (koishi@uw.edu)

Location and time

Day/Time: Thursday 6:30-9:20 pm; Place: Mary Gates Hall, room 231


The class will be graded based on Class participation (30%), HW (30%), and a (small) final project (40%). There are no exams.


Topics include molecular programming (DNA nanotchnology , DNA strand displacement cascades, Computing patterns, and introduction to chemistry), synthetic biology (Logic circuits, enzyme-based logic, pattern formation, computation with excitable cells, and introduction to gene regulation), and computation in the brain (introduction and basic neurobiology, neural encoding/decoding, and biophysical models of neurons).

Lecture Notes

You are encourage to print these lecture notes and bring them to class. They are the slides that will be used in class, and will be useful as starting points for you as you take notes during class.New slides will be added every week. Each "module" should cover roughly one hour of lecture but this can vary.

Module 0: Introduction
Module 1: DNA basics
Module 2: DNA origami
Module 3: Algorithmic self-assembly
Module 4: CRNs
Module 5: DSD circuits
Module 6: DSD circuits
Module 7: Central Dogma
Module 8: Synthetic biology
Module 8b: gene regulation notes
Module 9:CRISPR
Module 10: FSMs
Module 11: Stochastic simulations (Gillespie's algorithm)
Module 12: Gene circuit engineering
Module 13: Gro programming language
Module 14: Introduction to computational neuroscience; neurons
Module 15: Neural networks in machine learning
Module 16: Synapses and networks of neurons


All homeworks are due by the end of class on the date given.
Homework 1, Due January 16.
Homework 2, Due January 23.
Homework 3, Due January 30.
Homework 4, Due February 13.
Additional information for HW4
Homework 5, Due February 27.

Solution Sets

Homework 3 solution.

Upcoming classes

Thu 2/27:Neural networks in machine learning (guest lecture: Robert Gens, Domingos group)
Thu 3/6: TBA (guest lecture: Joel Zylberberg)

Final project

Grading: The project will be graded based on a written document and final presentation. Final project presentations will take place on the last day of class, March 3/13 and each presentation will be limited to *exactly* 3 min + 1 min of question. You will need to email me your slides (in ppt of keynote) but midnight of Wed 3/12. The written document should not exceed 2 pages (letter size, at least 11 pt font, 1 inch margin) of text plus 2 additional pages for figures, code, mathematical models and other supporting material.

Suggested scope: Identify a research paper that you find interesting and use one of the tools that were introduced in the class to model one of the systems described in that paper (e.g. if you chose the repressilator paper, you can use gro or stochastic simulations to model the oscillator dynamics). Creativity is encouraged: try to come up with interesting modifications to a system that is not discussed in your paper or create a new system that is "inspired" by a paper. A great project could also discuss if the proposed idea is realistic, compare it to exisiting work and use multiple approaches for simulating and understanding the system.