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Do modules or pathways help predict breast cancer outcome?

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If you have a question about this talk, please contact Florian Markowetz.

An important topic in systems biology is the identification of functional modules in protein-protein interaction networks by means of detecting jointly differentially expressed network regions. The first part of this talk is about an exact integer linear programming solution for subnetwork module detection (Dittrich et al., 2008). Recently, module and pathway based methods have also been proposed for breast cancer outcome prediction (e.g., Chuang et al., 2007, Lee et al., 2008). The second part of this talk addresses the performance of these methods on different established data sets using a unified validation procedure. Surprisingly, and contrary to previous claims, we find that current network or pathway based methods do not outperform a simple single gene-based classifier in terms of quality and stability.

This talk is part of the Seminars on Quantitative Biology @ CRUK Cambridge Institute series.

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