Access Type

Open Access Dissertation

Date of Award

January 2017

Degree Type


Degree Name



Computer Science

First Advisor

Sorin Draghici


A very important step in system biology is the identification of the networks that are most impacted in the given phenotype.

Such networks explain where the target genes are affected by some other genes, and therefore describe the mechanisms involved in a biological process.

The identified networks are used to: 1) predict the disease or the responses of the system to a specific impact, 2) find the subset of genes that interact with each other and play an important role in the condition of interest, and 3) understand the mechanisms involved in that condition.

In this thesis, we propose an approach that takes advantage of pre-defined pathways obtained from existing databases to identify the impact of a phenotype studied on such pathways.

Next, we introduce a method able to build a network that captures the putative mechanisms at play in the given condition, by using datasets from multiple experiments studying the same phenotype. This method takes advantage of known interactions extracted from multiple sources such as protein-protein interactions and curated biological pathways. Based on such prior knowledge, we overcome the drawbacks of snap-shot data by considering the possible effects of each gene on its neighbors.