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Searching for differentially expressed pathways in microarray data

Mathematical Systems Biology of Cancer II October 24, 2007 - October 26, 2007

October 24, 2007 (02:15 PM PDT - 03:00 PM PDT)
Speaker(s): Serban Nacu
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Abstract A typical microarray experiment compares two or several conditions (for example, cancer vs. normal cells) and produces a list of genes that are differentially expressed. The standard approach is to score each gene individually. However, real genes do not act alone: they interact in various ways, and cellular processes involve pathways that contain multiple genes. Many of those pathways and interactions are known. Hence an analysis that combines the microarray data with prior biological knowledge has the potential to be both more biologically relevant and statistically powerful. We survey some of the methods that have been proposed to address this problem, with a focus on algorithms based on interaction graphs.
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