Systematic approach for finding gene regulation signal mediators from large-scale experimental data
Name
Andreas Ellervee
Abstract
The goal of the thesis is to automatically find relations between genes from large heterogeneous experimental data. Depending on the type of the experiment, we can only find out very little about the actual regulation between genes. By combining different experiments we can determine the direct and indirect regulation of genes much more accurately.
With gene perturbation experiments we can identify genes, that the perturbed gene affects either directly or indirectly. If this data is combined with chromatin immunoprecipitation data, then we can separate directly affected genes from indirectly affected ones. The aim of this thesis is to find the intermediate regulators that carry the signal from the perturbed gene to the indirectly affected genes.
To find these intermediate regulators we combine ENCODE data with possible regulators and active promoters of genes. In case the gene’s regulatory area is shown to bind with a transcription factor, then we consider it a possible signal transmitter from the main regulator. As the end result, we will have regulatory triplets, where main regulator regulates an intermediate signal transmitter, that in return regulates the target gene.
The primary target of this thesis is to build a tool, which can find these regulatory triplets automatically given the proper input data.
Graduation Thesis language
Estonian
Graduation Thesis type
Bachelor - Computer Science
Supervisor(s)
Hedi Peterson, Elena Sügis
Defence year
2015