This course will cover statistical methods used to analyze data in experimental molecular biology, with an emphasis on gene and protein expression array data. Topics: data acquisition, databases, low level processing, normalization, quality control, statistical inference (group comparisons, cyclicity, survival), multiple comparisons, statistical learning algorithms, clustering visualization, and case studies.

Advisory Prerequisite: STATS,Graduate standing and STATS 400 (or equivalent)/permission of instructor. Students should have a strong preparation in either biology or some branch of quantitative analysis (mathematics, statistics, or computer science).