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140.687.11 GENE EXPRESSION DATA ANALYSIS

Cancelled

Department: Biostatistics
Term: Summer Inst. term
Credits: 2 credits
Academic Year: 2012 - 2013
Course Instructor:
  • Carlo Colantuoni
Description:

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.

Learning Objective(s):

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


Methods of Assessment: class exercises
Location: East Baltimore
Class Times:
  • 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
Enrollment Minimum: 10
Instructor Consent: No consent required
Prerequisite:

Students must have a basic understanding of biostatistical principles, including regression.

Grading Restriction: Letter Grade or Pass/Fail