140.687.11 GENE EXPRESSION DATA ANALYSIS
- Carlo Colantuoni
Introduces statistical concepts and tools necessary to analyze gene expression array data. Topics covered are basic data analysis, including background on gene expression measurement technology, basic microarray informatics, array normalization and bias adjustment, methods for computing gene expression indicators in oligonucleotide arrays, and methods for identifying genes that are differentially expressed across experiments. Also introduces survey methods for genome-wide analysis of expression patterns, including clustering, principal components, and binary classification algorithms such as discriminant analysis, recursive partitioning, and support vector machines.
Upon successfully completing this course, students will be able to define gene expression measurement technology, basic microarray informatics, array normalization and bias adjustment; assess survey methods for genome wide analysis
- Monday 1:30 - 5:00
- Tuesday 1:30 - 5:00
- Wednesday 1:30 - 5:00
- Thursday 1:30 - 5:00
- Friday 1:30 - 5:00
Students must have a basic understanding of biostatistical principles, including regression.