MIT8.591JF14 (24 files)
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Type: Course
Bibtex:
Tags:
Bibtex:
@article{,
title= {MIT OCW Systems Biology 8.591J Fall 14},
keywords= {},
journal= {},
author= {Jeff Gore},
year= {2014},
url= {https://ocw.mit.edu/courses/physics/8-591j-systems-biology-fall-2014/index.htm},
license= {},
abstract= {### 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.
### Prerequisites
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.
### Textbooks
Required Textbook
Alon, Uri. An Introduction to Systems Biology: Design Principles of Biological Circuits. Chapman & Hall / CRC, 2006. ISBN: 9781584886426. [Preview with Google Books]
Nowak, M. A. Evolutionary Dynamics: Exploring the Equations of Life. Belknap Press, 2006. ISBN: 9780674023383. [Preview with Google Books]
Supplementary Reading
Alberts, Bruce. Essential Cell Biology. Garland Science, 2009. ISBN: 9780815341291.
Strogatz, Steven H. Nonlinear Dynamics and Chaos: With Applications to Physics, Biology, Chemistry, and Engineering. Westview Press, 2014. ISBN: 9780813349107. [Preview with Google Books]
| LEC # | TOPICS | KEY DATES |
|-------|------------------------------------------------------------------------------------------------------|--------------------|
| 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 |
Instructor(s)
Prof. Jeff Gore
MIT Course Number
8.591J / 7.81J / 7.32
As Taught In
Fall 2014
Level
Undergraduate / Graduate},
superseded= {},
terms= {}
}
