Probabilistic Models for Gene Silencing Data (Probabilistische Modelle für RNA-Interferenz-Daten)

Florian Markowetz

Abstract: This thesis is concerned with signaling pathways leading to regulation of gene expression. I develop methodology to address two problems specific to gene silencing experiments: 1. gene perturbation effects cannot be controlled deterministically and have to be modeled stochastically. 2. direct observations of intervention effects on other pathway components are often not available. Gene silencing by RNAi has drastically reduced the time required for genome- wide screens for gene function, but no work has been done so far to adapt statistical methodology to the specific needs of RNAi data.