Date of Award

12-2019

Document Type

Thesis open access

Department

Computer Science

First Advisor

Matthew A. Hibbs

Second Advisor

Mark Lewis

Third Advisor

Paul Myers

Abstract

As technology advances, biologists are able to obtain more genetic information from experiments than ever before. As the amount of data they produce continues to increase, it is becoming more difficult to process the information and produce results that can be used in biological and medical research. One of the simplest ways to parse information quickly is through visualization. This project aims to improve the readability and utility of graph visualizations for biological pathway analysis by adding interactive and customizable components that allow biologists to determine what view of a dataset is most helpful to answer their questions.

This visualization strategy is being applied specifically to the Wnt signaling process, which is a form of cellular communication that is an area of active research. There is a lot of data about this process available, yet the fine details of Wnt signaling are often overlooked in common visualizations, despite its importance in cancers and other human diseases.

This project produced approximately 450 high level visualizations of Wnt signaling in human genetic datasets that are publicly available for use, and the code was made publicly available as well, so it might be extended to other pathways.

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