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High dimensional data analysis for new insight in ovarian cancer phenotypes

03 February 2010

PhD Ceremony: dhr. R.S.N. Fehrmann, 16.15 uur, Academiegebouw, Broerstraat 5, Groningen

Dissertation: High dimensional data analysis for new insight in ovarian cancer phenotypes

Promotor(s): prof.dr. A.G.J. van der Zee, prof.dr. E.G.E. de Vries

Faculty: Medical Sciences

Contact: via the UMCG, tel. 050-361 2200, e-mail: voorlichting@bvl.umcg.nl

This thesis focuses on the identification of gene-expression profiles, biological pathways and transcription factors that are associated with survival and chemo-resistance in ovarian cancer. We used currently available methods for predictive gene profiling identification, resulting in an 86-gene profile that was associated with overall survival. We also show that gene expression can be conceptualized as a process influenced by a limited set of Transcriptional System Regulators (TSRs). In addition, we show that an expression profile of an individual microarray can be fairly well predicted from only 50 TSR scores (TSR profiling), summarizing the signal of thousands of individual genes in just 50 component scores.

Last modified:15 September 2017 3.39 p.m.
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