Course Information

This course introduces important statistical models and computational algorithms in systems biology. Systems biology studies cellular and molecular processes, such as metabolism and signal transduction, in a systematic and quantitative manner. Topics include differential gene expression analysis of large scale microarray data sets, gene regulatory network modeling, and protein function prediction from protein-protein interaction network.

Homework and team projects will be assigned. Each group will make a final presentation of their projects.

• Meet 10:20-11:35am Tuesdays & Thursdays in Room SH 166
• Instructor: Dr. Joe Song, joemsong@cs.nmsu.edu, 505-646-4299
• Office: SH 141
• Office hours: 11:35-12:30am Tuesdays & Thursdays or by appointment.
• Course web page: www.cs.nmsu.edu/~joemsong/579
• Prerequisites: graduate standing in biology, computer science, mathematics, electrical & computer engineering, physics, or permission of instructor. A previous exposure in bioinformatics or computational biology will be helpful but is not required.

Text

• [required] Klipp et al, Systems Biology in Practice, 2005, Wiley. ( Amazon.com: new $120, used $88.99, www.addall.com: from $89.70)
• [recommended] Dhammika Amaratunga, Javier Cabrera, Exploration and Analysis of DNA Microarray and Protein Array Data, Wiley, 2003.
• [recommended] Alberts et al., Essential Cell Biology - An Introduction to the Molecular Biology of the Cell, Graland Publishing, 1998.
• [recommended] T.A. Brown, Genomes, 2nd Ed., Wiley-Liss, 2002.
• [recommended] Hiroaki Kitano (eds) Foundations of Systems Biology, 2001, MIT Press.
• Journals articles from Bioinformatics, J. of Computational Biology, J. of Bioinformatics and Computational Biology, Nucleic Acid Research, Genome Research, J. of Molecular Biology, and etc.
• Conference papers from ISMB, RECOMB, CSB, ECCB, PSB and etc.

Grading Policies

• About 3 sets of homework (45%).
• One team project (55%).
• Grading policies:
  • Homework is due two weeks after posted. Late homework will not be accepted.
  • No incomplete grades.

Topics

• Review of molecular biology and biochemistry
• Statistical analysis of microarray data

  The SAM test for differential gene expression analysis

• Computational models of gene regulatory networks

  Boolean networks, Bayesian networks, differential equations model

• Protein function prediction from protein-protein interaction networks

  Markov random fields model