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.
Recommended Citation
Roberts, Brian S., "Novel approaches to the analysis of gene regulation data" (2023). Dissertations. 365.
https://louis.uah.edu/uah-dissertations/365