This self-contained course will touch on many aspects of genome biology as it
applies to microarray analysis.
Topics include preprocessing, estimating gene expression levels, microarray data and
hybridization, experimental design, dimension reduction and pattern recognition
techniques including boosting, bagging and other recent statistical techniques for
microarray data analysis.
The course is computationally intensive and laboratory sessions are associated with methodology ones.