Title: "Detecting significant changes in the expression patterns of groups of genes"
Speaker: Dr. Michael (Mik) Black
Place: Mechanical Engineering Building (ME) 161; Tuesday, 4:30pm


Current approaches to the analysis of data from microarray experiments often focus on the detection of genes undergoing changes in expression between experimental conditions. Such analyses tend to assess significance on a per-gene basis, without incorporating any information about inter-gene relationships. Such information, however, is readily available, and can now be accessed through add-on packages in the R computing environment, making it easy to utilize in statistical analyses. This talk will provide an overview of working with gene annotation data within the Bioconductor framework, as well reviewing current approaches to detecting changes is the expression levels of grouped genes. Extensions to these approaches will also be presented, including methods for incorporating additional relational information into the analysis.

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