9.530 | Spring 2000 | Graduate

Cellular and Molecular Computation


1 Introduction and Overview. The Problem of Understanding Nonlinearity and Feedback in Biological Networks.
2 DNA Computing and Self-Assembly.
3 Enzyme Kinetics. Michaelis-Menten Theory. Cooperative Behavior.
4 Metabolic Control Analysis.
5 General Formalism for Chemical Reaction Networks. Metabolic Flux Analysis.
6 Student Presentations. Theory of Chemical Computation.
7 Overview of Transcriptional Regulation. Lambda Phage.
8 Models of Bistability in Chemical Reaction Networks.
9 Demo of Bard Ermentrout’s XPP. Chemical Reaction Networks Versus Neural Networks. Global Stability of Symmetric Networks.
10 Student Presentations. Synthetic Genetic Networks.
11 Oscillations in an Activator-Inhibitor System. Phase Plane Analysis.
12 Hodgkin-Huxley Model of the Action Potential.
13 Spike Frequency Adaptation and Negative Feedback Linearization.
14 Phototransduction.
15 Chemotaxis.
16 Long-Term Potentiation.
17 Circadian Rhythms.
18 Stochastic Models of Lambda Phage.
19 Molecular Motors.
20 Development.
21 Cell Cycle.
22 Pattern Formation and Slime Molds.
23 Cell Sorting.
24 Immunity.
25 Final Project Presentations.

Course Info

As Taught In
Spring 2000