Pattern recognition of gene expression data on signalling networks of cancer [Elektronische Ressource] / presented by Kannabiran Nandakumar

Dissertation submitted to the Combined Faculties for the Natural Sciences and for Mathematics of the Ruperto-Carola University of Heidelberg, Germany for the degree of Doctor of Natural Sciences Presented by: Kannabiran Nandakumar M.Sc. Birth place : Chennai, India February, 2010 Pattern recognition of gene expression data on signalling networks of cancer Supervisor : Dr. Rainer König Referees : Prof. Dr. Roland Eils Prof. Dr. Manfred Schwab Abstract Cancer is a result of aberrant cellular signalling. Understanding the properties of these complex networks will enable us to design effective therapeutic strategies against cancer. Often, singular pathways are analyzed to study cancer signalling. This kind of analysis eludes the idea of orchestrated roles of signalling proteins in a network. In the analysis presented in this thesis, a network approach is used to obtain an understanding of the intricate cellular signalling. In this thesis a sophisticated embedding of human cancer gene expression data onto the human protein-protein interaction network has been performed and pathways were predicted using a graph theoretic approach. Several network properties of normal and cancer signalling were derived from these predicted pathways using 10 cancer datasets.