140.687.11
Gene Expression Data Analysis
Course Status
Cancelled
Course Status
Cancelled
Location
East Baltimore
Term
Summer Institute
Department
Biostatistics
Credit(s)
2
Academic Year
2013 - 2014
Instruction Method
TBD
M, Tu, W, Th, F, 1:30 - 5:00pm
Available to Undergraduate
No
Grading Restriction
Letter Grade or Pass/Fail
Course Instructor(s)
Carlo Colantuoni
Frequency Schedule
Every Year
Resources
Prerequisite
Students must have a basic understanding of biostatistical principles, including regression.
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.