Modeling and Analysis of Biological Networks
With the sequencing of the human genome and the genomes of other organisms,
we now have a list of the parts that make up these biological systems.
Through the use of microarrays and other new technologies, we are also
beginning to get data on the functions of individual genes and how genes
interact with each other to perform complex biological functions. In the
functional genomic era, we will begin to take this vast amount of data, and
try to reason about how these genetic systems work. To accomplish this, a
systems biology perspective will need to be taken in which models and new,
efficient analysis techniques will need to be developed to reason about these
genetic networks. Engineers have had vast experience in modeling and analyzing
electronic circuits and systems. It is not difficult to develop a view of a
genetic network as a electronic circuit. Such a view was taken by McAdams and
Shapiro in their seminal paper in Science in 1995 with encouraging results.
Therefore, as in the sequencing of the human genome, collaborations between
engineers and systems biologists will be essential to the success of functional
genomics. In this new course, we will be reading papers on recent approaches
to the modeling and analysis of biological networks. The goal of this course is
to be useful to both engineers and computer scientists who wish to learn about
biological problems to which their models can be applied and to biologists and
bioengineers who would like to learn about models and analysis techniques that
can be used to study their systems of interest.
Instructor: Dr. Chris
Students must have either taken a course(s) in genetics, cell biology,
molecular biology, or biochemistry (examples include Biol 2020, 2030, 3510,
5011, 5110, 5255, 5265), or you must have taken a course(s) in formal modeling
(examples include ECE 5750/6750, CS 5100, CS 5350, CS 6110).
A Genetic Switch by Mark Ptashne published by Cell and BSP.
The grading for this course will be broken into two parts: course participation
and final project. The grade for course participation will be dependent upon
attendence, participation in discussion of required readings, leading of
discussions for optional readings, homework assignments, and possibly quizes.
In the final project, students must select a modeling methodology and a sample
biological system and attempt to model and analyze this system using this
||3:30pm - 4:30pm
||3:20pm - 4:50pm
||2pm - 3pm
All information here is tentative.
- Week 1: Introduction
- Week 2: Phage Lambda
- Read Chapters 1 through 3 of A Genetic Switch (required).
- Read Chapter 4 of A Genetic Switch (optional).
- Lecture 2
- Week 3: Systems Biology
- Read de Jong (required).
- Read Baldi and Hatfield, DNA Microarrays and Gene Expression,
Chapter 8 Systems Biology, handed out in class (required).
- Read D'haeseleer (optional).
- Read Hasty (optional).
- Read Arkin (optional).
- Read Arkin 2 (optional).
- Read Endy (optional).
- Read Fitch (optional).
- Read Smolen et. al, Modeling transcriptional control in gene networks:
methods, recent results, and future directions, 2000 B. Math. Biol.,
62:247-292, find in libraryec
- Read Bower and Bolouri, eds. 2001. Computational Modeling fo Genetic and Biochemical Networks, MIT Press, Cambridge, MA (optional).
- Lecture 3
- Please read these week2 reports
- Weeks 4 and 5: Chemical Master Equation
- Weeks 6 and 7: Differential Equations
- Weeks 8 and 9: Circuit Networks
- Week 10: Bayesian Networks
- Week 11: Miscellaneous Learning Methods
- Week 12: Directed Graphs and Pathway Databases
- Week 13: Flux Balance Analysis
- Week 14: Engineered Gene Circuits
- Week 15: Project Presentations
Related Web Pages