Date of Award

2023

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Biotechnology Science and Engineering

Committee Chair

Richard M. Myers

Committee Member

Matthew L. Niemiller

Committee Member

Gregory M. Cooper

Committee Member

Paul G. Wolf

Committee Member

Jerome Y. Baudry

Subject(s)

Gene expression, Genetic regulation, Genetic transcription, Big data--Analysis

Abstract

The study of gene regulation is crucial to understanding differentiation, cell specialization, and response to external stimuli observed in multicellular organisms. Genome-scale technologies enabled by high-throughput sequencing have allowed insight into many aspects of gene regulation. However, these techniques produce large, complex data that require the development of computation-based analytical techniques. I present here two analytical techniques that I have created for gene regulation data. First, I describe an approach for the analysis of sequencing-based reporter data that reveals new features of human genetic sequence that generate biased strand transcription even out of genomic context. Next, I present a package of analytical tools for associating genomic regulatory regions with gene expression changes caused by a perturbation. I demonstrate its application to three data sets yielding credible and impactful results. Both these methods represent important contributions to furthering the understanding of gene regulation.

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.