BioE 594
-- Design and Implementation of Computational Methods in
Bioinformatics
12:30am-13:45pm Tuesdays and Thursdays
Room : 419 CMW (College of Medicine West)
Instructor: Yang Dai (yangdai@uic.edu)
Office Hours : 2:00pm -3:00pm, Tuesdays
Office Location :
Room W125
Medical Sciences Building
835 S. Wolcott Ave.
Tel : (312)413-1487
Share the entrance with
CLIMB Clinical Laboratory for Interfacial Molecular Bioengineering
Quick Links
Course Description
This semester we focus on learning methods of genomic data mining and machine learning. Their applications are introduced mostly around the analysis
of microarray data. Special topics includes cancer subtype prediction, genetic network prediction, protein function prediction.
Course Requirements
Required background includes ability to program in a high-level language.
S-Plus(or R) or Matlab experience may also be helpful.
Homework assignments may include reading, mathematical analysis, programming, and the use of software tools.
Student will be asked to present papers from the literature. Students will also need to complete a term project, and produce both a written final report and a class presentation.
Grading Policy
Class participation and discussion (10%)
Homework assignments (35%)
Term project (30%)
One exam (25%)
final exam on ?
final project presentation on April 26,28
Required Software (Base, upon which analysis tools will be used and built)
- Matlab (available from ACCC)
- R (download from here) and others.
Please make sure that you are familiar with them. Homework assignments are based on them.
Topics
- Primer on Molecular Genetics
- Microarray Technology
- Microarray experiments
- Preprocessing of Microarray data
- Resampling and bootstrap
- R and Bioconductor
- Multiple testing
- Distances and expression measures
- Feature selection techniques
- Cluster analysis in microarray experiments
- Classification in microarray experiments
- Inferring genetic network
- Protein function prediction
Schedule and materials presented
Reading
Reference Books
(1) Microarray Bioinformatics, by Dov Stekel, Cambridge University Express, 2003.
(2) Microarray for an Integrative Genomics, by Issac S, Kohane et al.,
The MIT Press, 2003. ISBN 0-262-11271-X.
(3) Biostatistics : a fundation for analysis in the health sciences, 7th edition, by W. Daniel,
John Wiley, 1999.
(4) Pattern Recognition, by S. Theodoridis and K. Koutroumbas, Academic Press, 1999.
Additional Online Reading Materials
- Statistics
- R References
- Molecular Biology
- DNA Chip Technology
-
Animation ( it's fun! )
-
Nature Genetics 21 (1) 1999 (In this issue you will find a series of state-of-the-art reviews of the technology
for production of DNA chips in various formats. Also it is published in 1999, many basic concepts
of the technology remains unchanged)
- Support Vector Machine
Major microarray databases
Stanford microarray database
Analysis tools for microarray data
SMD Microarray Links : Software & Tools
Bioconductor
Articles on Microarray Datamining:
Wentian Li of Rockefeller University maintains a list of papers on data analysis:
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