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BIST-535-01 Case Studies in Bioinformatics
Fall only
Course Description: 3 one-unit modules, each covering a different topic: e.g., microarray data analysis, phylogenetic analysis, and proteomics.
1. Microarray Data Analysis: Microarray technology will be introduced, and the different platforms described. Statistical issues in microarray experiments include: experimental design, sample size calculations, pre-processing and data cleansing, differential expression testing, clustering and prediction. S-PLUS, R and the Bioconductor project, including many statistical and graphical methods that are appropriate in the analysis of microarray data, will be introduced.
2. Phylogenetic Analysis: mutation, evolution, selection, properties of trees, topologies, distance metrics, clustering, distance-based methods, character-based methods, evolutionary models, maximum likelihood estimation, Bayesian approach.
3. Proteomics: technology for 2D gels analysis and mass spectra, biomarker discovery, preprocessing, differential-expression analysis, classification, clustering.
Credits: 3
Prerequisites: BIST-510 and BIST-511, or by permission
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