Course Meeting Times

Lectures: 2 sessions / week, 1.5 hours / session

Course Description

This course provides an introduction to cellular and population-level systems biology with an emphasis on synthetic biology, modeling of genetic networks, cell-cell interactions, and evolutionary dynamics. Cellular systems include genetic switches and oscillators, network motifs, genetic network evolution, and cellular decision-making. Population-level systems include models of pattern formation, cell-cell communication, and evolutionary systems biology.


Given the wide range of backgrounds among students in this class we will try to avoid unnecessary jargon and mathematics. However, it will be very helpful if you are comfortable with the material in Introductory Biology 7.012, Differential Equations 18.03, and Probability 18.05. In addition, each weekly problem set will have a computational problem, so prior experience with a computational package such as MATLAB®, Mathematica®, or Python is expected. The "officially supported" package will be Python (sample code, etc), but problems can be done in any language.


Required Textbook

Buy at Amazon Alon, Uri. An Introduction to Systems Biology: Design Principles of Biological Circuits. Chapman & Hall / CRC, 2006. ISBN: 9781584886426. [Preview with Google Books]

Buy at Amazon Nowak, M. A. Evolutionary Dynamics: Exploring the Equations of Life. Belknap Press, 2006. ISBN: 9780674023383. [Preview with Google Books]

Supplementary Reading

Buy at Amazon Alberts, Bruce. Essential Cell Biology. Garland Science, 2009. ISBN: 9780815341291.

Buy at Amazon Strogatz, Steven H. Nonlinear Dynamics and Chaos: With Applications to Physics, Biology, Chemistry, and Engineering. Westview Press, 2014. ISBN: 9780813349107. [Preview with Google Books]

Pre-class Reading Questions

To facilitate interactions during class between students, we will have short required questions about the reading that will be due before class.


The course will have weekly problem sets (due at the end of each week), two midterms, and a final. The grading breakdown is as follows:

Problem sets 40%
Pre-class reading questions 5%
Midterm 1 15%
Midterm 2 15%
Final Exam 25%


1 Introduction to the class and overview of topics. Basic concepts in networks and chemical reactions.  
2 Input function of a gene, Michaelis-Menten kinetics, and cooperativity  
3 Autoregulation, feedback and bistability Problem Set 1 due
4 Introduction to synthetic biology and stability analysis in the toggle switch  
5 Oscillatory genetic networks Problem Set 2 due
6 Graph properties of transcription networks  
7 Feed-forward loop network motif Problem Set 3 due
8 Introduction to stochastic gene expression  
9 Causes and consequences of stochastic gene expression Problem Set 4 due
10 Stochastic modeling—The master equation, Fokker-Planck Equation, and the Gillespie algorithm  
11 Life at low Reynold’s number Problem Set 5 due
12 Robustness and bacterial chemotaxis  
  No Lecture Midterm 1
13 Robustness in development and pattern formation Problem Set 6 due
14 Introduction to microbial evolution experiments, and optimal gene circuit design  
15 Evolution in finite populations, genetic drift, and the theory of neutral molecular evolution Problem Set 6 due
16 Clonal interference and the distribution of beneficial mutations  
17 Fitness landscapes and sequence spaces Problem Set 7 due
18 Evolutionary games  
  No Lecture Midterm 2
19 Survival in fluctuating environments Problem Set 8 due
20 Parasites, the evolution of virulence and sex  
21 Interspecies interactions, the Lotka-Volterra model, and predator-prey oscillations Problem Set 9 due
22 Ecosystem stability, critical transitions, and the maintenance of biodiversity  
23 Dynamics of populations in space Problem Set 10 due
24 The neutral theory of ecology  
    Final Exam