Meta-analysis of Cancer Gene Profiling Data

  • Janine Roy
  • Christof Winter
  • Michael SchroederEmail author
Part of the Methods in Molecular Biology book series (MIMB, volume 1381)


The simultaneous measurement of thousands of genes gives the opportunity to personalize and improve cancer therapy. In addition, the integration of meta-data such as protein-protein interaction (PPI) information into the analyses helps in the identification and prioritization of genes from these screens.

Here, we describe a computational approach that identifies genes prognostic for outcome by combining gene profiling data from any source with a network of known relationships between genes.

Key words

Network-based Outcome prediction Gene expression PageRank Cancerbiomarker 



We kindly acknowledge funding from EU, DFG, BMWi (PPI-Marker, OpenScienceLink, SigSax, GeneCloud).


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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Janine Roy
    • 1
  • Christof Winter
    • 2
  • Michael Schroeder
    • 1
    Email author
  1. 1.Biotechnology CenterTechnische Universität DresdenDresdenGermany
  2. 2.Faculty of Medicine, Department of Clinical Sciences, Oncology MVUniversity of LundLundSweden

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