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Abstract/Syllabus:
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van Oudenaarden, Alexander, 8.591J Systems Biology, Fall 2004. (Massachusetts Institute of Technology: MIT OpenCourseWare), http://ocw.mit.edu (Accessed 09 Jul, 2010). License: Creative Commons BY-NC-SA
Fall 2004
Diagram of the chemotactic pathway in E. coli. (Figure by MIT OCW. After figure 4 in Falke, J. J., R. B. Bass, S. L. Butler, S. A. Chervitz, and M. A. Danielson. "The Two-component Signaling Pathway of Bacterial Chemotaxis: A Molecular View of Signal Transduction by Receptors, Kinases, and Adaptation Enzymes." In Annu Rev Cell Dev Biol. 13 (1997): 457-512.)
Course Highlights
This course features a set of course notes in the readings section.
Course Description
This course introduces the mathematical modeling techniques needed to address key questions in modern biology. An overview of modeling techniques in molecular biology and genetics, cell biology and developmental biology is covered. Key experiments that validate mathematical models are also discussed, as well as molecular, cellular, and developmental systems biology, bacterial chemotaxis, genetic oscillators, control theory and genetic networks, and gradient sensing systems. Additional specific topics include: constructing and modeling of genetic networks, lambda phage as a genetic switch, synthetic genetic switches, circadian rhythms, reaction diffusion equations, local activation and global inhibition models, center finding networks, general pattern formation models, modeling cell-cell communication, quorum sensing, and finally, models for Drosophila development.
Technical Requirements
MATLAB® software is required to run the .m files found on this course site.
Syllabus
Overview
The goal of this course is to help students develop a quantitative understanding of the biological function of genetic and biochemical networks. Students will be provided with the essential mathematical tools needed to model network modules, such as biological switches, oscillators, filters, amplifiers, etc. An array of example biological problems that can be successfully tackled with a systems biology approach will be introduced by discussing recent papers on the subject. The intrinsic challenge of this class is that students are coming in with wildly different backgrounds. Read up on your biology or math if needed. Use time in the recitations to help close some of the knowledge gaps and to help you prepare for the homework.
There are three levels of complexity to Systems Biology:
- I Systems Microbiology (14 Lectures) 'The cell as a well-stirred biochemical reactor'
- II Systems Cell Biology (8 Lectures) 'The cell as a compartmentalized system with concentration gradients'
- III Systems Developmental Biology (3 Lectures) 'The cell in a social context communicating with neighboring cells'
Text
The course notes serve as the text. For good biology reference texts, see:
Alberts, Bruce, et. al. Molecular Biology of the Cell. 4th ed. New York: Garland Science, 2002. ISBN: 9780815332183.
Lodish, Harvey, et al. Molecular Cell Biology. 5th ed. New York: W. H. Freeman and Company, 2003. ISBN: 9780716743668.
Assignments, Exams, and Grading
MATLAB® will be used intensively during the course. Make sure you know or learn how to use it as it is necessary for the problem sets.
There are 5 problem sets and one take home final for the course. The grading breakdown is as follows:
AssIGNMENTS |
PERCENTAGES |
Problem set 1 |
15% |
Problem set 2 |
15% |
Problem set 3 |
15% |
Problem set 4 |
15% |
Problem set 5 |
15% |
Final |
25% |
Calendar
LEC # |
TOPICS |
KEY DATES |
Part I: Systems Microbiology - 'The Cell as a Well-stirred Bioreactor' |
1 |
Introduction Michaelis-Menten Kinetics |
|
2 |
Equilibrium Binding Cooperativity |
|
3 |
Lambda Phage Multistability |
|
4 |
Multistability (cont.) |
|
5 |
Synthetic Genetic Switches |
|
6 |
Stability Analysis |
|
7 |
Introduction E. coli Chemotaxis |
|
8 |
Fine-tuned versus Robust Chemotaxis Models |
Problem set 1 due |
9 |
Wrapping up Chemotaxis |
|
10 |
Genetic Oscillators |
|
11 |
Genetic Oscillators (cont.) |
|
12 |
Stochastic Chemical Kinetics |
Problem set 2 due |
13 |
Stochastic Chemical Kinetics (cont.) |
|
Part II: Cell Systems Biology - 'The Importance of Diffusion and Gradients for Cellular Regulation' |
14 |
Introduction Cell Systems Biology Fick's Laws |
|
15 |
Local Excitation Global Inhibition Theory |
|
16 |
Local Excitation (cont.) Global Inhibition Theory (cont.) |
Problem set 3 due |
17 |
Rapid Pole-to-pole Oscillations in E. coli |
|
18 |
Rapid Pole-to-pole Oscillations in E. coli (cont.) |
|
19 |
Models for Eukaryotic Gradient Sensing |
Problem set 4 due |
20 |
Models for Eukaryotic Gradient Sensing (cont.) |
|
21 |
Modeling Cytoskeleton Dynamics |
|
22 |
Modeling Cytoskeleton Dynamics (cont.) |
Problem set 5 due |
Part III: Developmental Systems Biology - 'Building an Organism Starting From a Single Cell' |
23 |
Quorum Sensing |
|
24 |
Final Problem Set Question Hour |
|
25 |
Drosophila Development |
Take home final due |
|
|
|
Further Reading:
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Readings
MATLAB® software is required to run the .m files in this section.
Suggested Readings in Biology
The following sections from Alberts, Bruce, et al. Molecular Biology of the Cell. 4th ed. New York: Garland Science, 2002. ISBN: 9780815332183, are suggested:
-
RNA and Protein Synthesis
-
Overview of Gene Control
-
How Genetic Switches Work
-
General Principles of Cell Signaling
Downloadable course notes are included courtesy of Prof. Alexander van Oudenaarden as well as any additional authors noted in the table below.
LEC # |
TOPICS |
READINGS |
Part I: Systems Microbiology - 'The Cell as a Well-stirred Bioreactor' |
1 |
Introduction
Michaelis-Menten Kinetics |
|
2 |
Equilibrium Binding
Cooperativity |
Michaelis-Menten Kinetics Associated MATLAB® code file (M) |
3 |
Lambda Phage
Multistability |
A Genetic Switch in Lamba Phage Associated MATLAB® code file (M)
Hasty, Jeff, Joel Pradines, Milos Dolnik, and J. J. Collins. "Noise-based Switches and Amplifiers for Gene Expression." Proc. Natl. Acad. Sci. USA 97, no. 5 (Feb 29, 2000): 2075-80. |
4 |
Multistability (cont.) |
Isaacs, Farren J., Jeff Hasty, Charles R. Cantor, and J. J. Collins. "Prediction and Measurement of an Autoregulatory Genetic Module." PNAS 100, no. 13 (June 24, 2003): 7714-19. |
5 |
Synthetic Genetic Switches |
Synthetic Genetic Switches Gardner, Timothy S., Charles R. Cantor, and James J. Collins. "Construction of a Genetic Toggle Switch in Escherichia coli." Nature 403, no. 6767 (January 20, 2000): 339-42. |
6 |
Stability Analysis |
Stability Analysis |
7 |
Introduction E. coli Chemotaxis |
|
8 |
Fine-tuned versus Robust Chemotaxis Models |
Modeling Escherichia coli chemotaxis Associated MATLAB® code file (M) Spiro, Peter A., John S. Parkinson, and Hans G. Othmer. "A Model of Excitation and Adaptation in Bacterial Chemotaxis." Proc. Natl. Acad. Sci. USA 94, no. 14 (July, 1997): 7263–68. |
9 |
Wrapping up Chemotaxis |
Biological Oscillators |
10 |
Genetic Oscillators |
Biological Oscillators Associated MATLAB® code file (M)
Elowitz, Michael B., and Stanislas Leibler. "A Synthetic Oscillatory Network of Transcriptional Regulators." Nature 403, no. 6767 (January 20, 2000): 335-8. |
11 |
Genetic Oscillators (cont.) |
Routh-Hurwitz Associated MATLAB® code file (M)
Atkinson, Mariette R., Michael A. Savageau, Jesse T. Myers, and Alexander J. Ninfa. "Development of Genetic Circuitry Exhibiting Toggle Switch or Oscillatory Behavior in Escherichia coli." Cell 113, no. 5 (May 30, 2003): 597-607. |
12 |
Stochastic Chemical Kinetics |
The Origin and Consequences of Noise in Biochemical Systems (Courtesy of Alexander van Oudenaarden and Mukund Thattai. Used with permission.) |
13 |
Stochastic Chemical Kinetics (cont.) |
|
Part II: Cell Systems Biology - 'The Importance of Diffusion and Gradients for Cellular Regulation' |
14 |
Introduction Cell Systems Biology
Fick's Laws |
|
15 |
Local Excitation
Global Inhibition Theory |
Local Excitation, Global Inhibition Model |
16 |
Local Excitation (cont.)
Global Inhibition Theory (cont.) |
|
17 |
Rapid Pole-to-pole Oscillations in E. coli |
Howard, Martin, Andrew D. Rutenberg, and Simon de Vet. "Dynamic Compartmentalization of Bacteria: Accurate Division in E. Coli." Physical Review Letters 87, no. 27 (December 31, 2001). |
18 |
Rapid Pole-to-pole Oscillations in E. coli (cont.) |
|
19 |
Models for Eukaryotic Gradient Sensing |
Models for Eukaryotic Gradient Sensing Associated MATLAB® code file (M) Narang, Atul, K. K. Subramanian, and D. A. Lauffenburger. "A Mathematical Model for Chemoattractant Gradient Sensing based on Receptor-regulated Membrane Phospholipid Signaling Dynamics." Annals of Biomedical Engineering 29, no. 8 (2001): 677-91. |
20 |
Models for Eukaryotic Gradient Sensing (cont.) |
Postma, Marten, and Peter J. M. Van Haastert. "A Diffusion–Translocation Model for Gradient Sensing by Chemotactic Cells." Biophysical Journal 81, no. 3 (September, 2001): 1314-23. |
21 |
Modeling Cytoskeleton Dynamics |
Dogterom, Marileen, and Stanislas Leibler. "Physical Aspects of the Growth and Regulation of Microtubule Structures." Physical Review Letters 70, no. 9 (March 1, 1993). |
22 |
Modeling Cytoskeleton Dynamics (cont.) |
Cytrynbaum, E. N., V. Rodionov, and A. Mogilner. "Computational Model of Dynein-dependent Self-organization of Microtubule Asters." Journal of Cell Science 117, no. 8 (March 15, 2004): 1381-97. |
Part III: Developmental Systems Biology - 'Building an Organism Starting From a Single Cell' |
23 |
Quorum Sensing |
You, Lingchong, Robert Sidney Cox III, Ron Weiss, and Frances H. Arnold. "Programmed Population Control by Cell-Cell Communication and Regulated Killing." Nature 428, no. 6985 (April 22, 2004): 868-71. |
24 |
Final Problem Set Question Hour |
|
25 |
Drosophila Development |
Houchmandzadeh, Bahram, Eric Wieschaus, and Stanislas Leibler. "Establishment of Developmental Precision and Proportions in the Early Drosophila embryo." Nature 415, no. 6873 (February 14, 2002): 798-802. |
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