JSM 2004 - Toronto

Abstract #300246

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Activity Number: 97
Type: Invited
Date/Time: Monday, August 9, 2004 : 10:30 AM to 12:20 PM
Sponsor: WNAR
Abstract - #300246
Title: Slippery Phenotypes: Survival Analysis Using Microarrays
Author(s): Marco Ramoni*+ and Paola Sebastiani
Companies: Harvard Medical School and Boston University
Address: Harvard Partners Center for Genetics and Genomics, Boston, MA, 02115,
Keywords: microarrays ; Bayesian statistics ; survival analysis
Abstract:

The development of microarray technology presents unprecedented opportunities to discover new aspects of human diseases and to deliver new drugs and new diagnostic methods. An emerging challenge for this endeavor is the characterization of clinical features--such as survival time--that do not easily fall into discrete categories. Traditional survival analysis methods have been sometimes successful in analyzing some survival genomic experiments, they are unable to account for biological and sample variability and rest on the unrealistic assumption that the expression of each gene is functionally independent of the expression of other genes. This talk describes a Bayesian approach to the joint analysis of gene expression data and survival time in microarray experiments that can overcome these limitations. The novelty of this approach is that it is able to integrate survival time and gene expression data while accounting for both the variability of gene expression and the functional dependencies among genes.

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Revised March 2004