COMP 572 / BIOS 572 / BIOE 564
BIOINFORMATICS: NETWORK ANALYSIS
Fall 2009

Staff

Course Information

• MEETING PLACE AND TIME: KH 107, Tuesday and Thursday, 2:30-3:50.
• TEXTBOOK: The following two books are recommended for the course, but are also highly recommended if you are interested in computational network analysis techniques. Both books should be available from the Rice University bookstore in time for the Fall semester.
  1. Biological Networks, F. Kepes (Editor), World Scientific Publishing Company, 2008 (ISBN: 978-9-81270-695-9).
  2. Protein-protein Interactions and Networks, A. Panchenko and T. Przytycka (Editors), Springer, 2008 (ISBN: 978-1-84800-124-4).
• INTENDED AUDIENCE: anyone who's interested in learing about computational techniques for analyzing biological networks. The course will be taught in such a way so as to make it accessible to students from different backgrounds (biology, math, CS, engineering, TMC institutions,...).
• TOPICS TO BE COVERED: (As time permits)
  1. Networks and their inference.
  2. Graph-theoretic concepts and connectivity-based properties.
  3. Random networks and network motifs.
  4. Robustness of networks.
  5. Community structure in networks.
  6. Analysis of protein-protein interaction networks.
  7. Comparative network analysis (network alignment).
  8. Signal transduction networks.
  9. Transcription regulation networks.
  10. Metabolic networks.
  11. Ecological networks.
  12. Phylogenetic networks.
• GRADING:
  • A set of homework assignments: 50%. These assignments will simply test understanding of the material covered in class, and may require very "light-weight" programming (mostly using a scripting language, such as Perl, Matlab, etc.).
  • Course project: 50%. The project has to include elements of network analysis. It could be analysis of the performance of different techniques, analysis of a biological system of interest, the performance of a certain technique on a specific type of network data, etc. There is NO requirement that the project should involve heavy programming, and any programming language and/or environment can be used (C, C++, Java, Matlab, R, etc.).
• STUDENTS WITH DISABILITY: Any student with a documented disability needing academic adjustments or accommodations is requested to speak with me during the first two weeks of class. All discussions will remain confidential. Students with disabilities will need to also contact Disability Support Services in the Ley Student Center.

Course Material

• A list of resources for biological network analysis.
• For the course on graphs and networks in systems biology, taught by Reka Albert at Penn State University, click here.
• For the course on analysis of biological networks, taught by Roded Sharan at Tel Aviv University, click here.

1. Homework assignment #1: PDF. Due date: Sep 22.
2. Homework assignment #2: PDF. Due date: Oct 15.
3. Homework assignment #3: PDF. Due date: Dec 3.
4. Homework assignment #4: PDF. Due date: Dec 3.