Author ORCID Identifier
0000-0001-6278-1074
Date of Award
5-1-2023
Degree Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
Computer Science
First Advisor
Alex Zelikovsky
Second Advisor
Pavel Skums
Third Advisor
Murray Patterson
Fourth Advisor
Artem Rogovskyy
Abstract
Metabolic pathways are a series of enzyme-mediated reactions that result in the transformation of substances from one form to another. While methods for studying metabolic pathways are constantly improving, analyzing these pathways can be challenging. To accurately predict metabolic pathway activity, it is essential to understand and quantify the relative involvement of enzymes in these pathways. In my dissertation, I propose a novel method based on the maximum likelihood Expectation-Maximization (EM) algorithm to estimate metabolic pathway activity levels using enzyme participation as a latent variable. This improved maximum likelihood model will be used to conduct downstream analysis of metabolic pathway expression, which will be estimated from RNA-Seq samples obtained from rodents and a planktonic microbial community.
DOI
https://doi.org/10.57709/35365476
Recommended Citation
Rondel, Filipp, "Expectation Maximization Methods for Metabolic Pathway Analysis." Dissertation, Georgia State University, 2023.
doi: https://doi.org/10.57709/35365476
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