Date of Award
Master of Science (MS)
In this project, I present approaches to rank Transcription Factors (TFs) based on their direct and indirect regulation of a given set of genes. I present two methods: the first is a classical test of overlap approach, while the second uses a network flow algorithm. Moreover, I present a novel randomization approach based on a non-uniform background model to which the results of each method are compared to produce a more robust ranking. The proposed methods are applied on data sets associated with the Mediator protein complex where we aimed to identify the different TFs that are primarily responsible for causing the variations in gene expression when two of the Mediator’s proteins CDK8 and CDK19 are knocked down. The results showed different TFs rankings between the different proteins. My ranking system will be useful for nominating the TFs to be tested experimentally by biologists to certify the main TFs responsible for the difference in gene expression.
Alhazzani, May, "A ranking approach of transcription factors based on their direct and indirect significance in gene regulatory networks" (2014). Computer Science Graduate Theses & Dissertations. 93.