Date of Award

9-22-2025

Document Type

Dissertation

Degree Name

Molecular Biosciences, Ph.D.

First Advisor

Jason Causey

Committee Members

Jake Qualls; Jonathan Stubblefield; Karl Walker; Xiuzhen Huang

Abstract

The publication of the human genome in 1994 launched a computational biology revolution. Despite subsequent advances in sequencing and computing technology, the research community lacks robust and reproducible tools for interpreting differential expression of genes. Modern high-throughput genome sequencing and high-density arrays allow unprecedented computational analysis of genetic profiles. These developments combined with the rise artificial intelligence and machine learning powered by unprecedented amounts of data present new opportunities in bioinformatics. A novel gene ranking method, AUCg, is presented and applied to genetic expression data from patients with multiple myeloma. The AUCg method is compared to popular Bioconductor tools, and the corresponding advantages and drawbacks are discussed. Other recently developed tools including PyDESeq2 and Bioinfokit are also implemented, resulting in the identification of significantly over- and under-expressed genes that may serve as therapeutic targets. Finally, a review of the known roles and interactions of identified genes offers new insight to the disease biology and progression of multiple myeloma.

Rights Management

Creative Commons Attribution-NonCommercial 4.0 International License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

Share

COinS
 
 

To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.