Abstract
Protein networks are increasingly used to enrich our knowledge about disease by integrating diverse information sources such as sequence and expression data into one computational framework. In this talk I will describe two recent works that use network propagation to associate novel genes and modules with disease. I will demonstrate how the propagation methodology allows processing raw mutation and expression signals to infer disease components that cannot be readily revealed from the measured molecular data.
This is joint work with the labs of Mehmet Koyuturk and Erich Wanker.