Google Goes Cancer: Improving Outcome Prediction for Cancer Patients by Network-Based Ranking of Marker Genes

@inproceedings{Winter2012GoogleGC,
  title={Google Goes Cancer: Improving Outcome Prediction for Cancer Patients by Network-Based Ranking of Marker Genes},
  author={Christof Winter and Glen Kristiansen and Stephan Kersting and Janine Roy and Daniela Aust and Thomas Kn{\"o}sel and Petra R{\"u}mmele and Beatrix Jahnke and Vera Hentrich and Felix R{\"u}ckert and Marco Niedergethmann and Wilko Weichert and Marcus Bahra and Hans J. Schlitt and Utz Settmacher and Helmut Friess and Markus W. B{\"u}chler and Hans-Detlev Saeger and Michael Schroeder and Christian Pilarsky and Robert Gr{\"u}tzmann},
  booktitle={PLoS Computational Biology},
  year={2012}
}
Predicting the clinical outcome of cancer patients based on the expression of marker genes in their tumors has received increasing interest in the past decade. Accurate predictors of outcome and response to therapy could be used to personalize and thereby improve therapy. However, state of the art methods used so far often found marker genes with limited prediction accuracy, limited reproducibility, and unclear biological relevance. To address this problem, we developed a novel computational… CONTINUE READING
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