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Threshold Functions for Modeling Gene Regulatory Networks
Kittaneh, Hadeel Ali
Kittaneh, Hadeel Ali
Date
2024-06
Author
Advisor
Type
Thesis
Degree
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29.232-2024.04a Hadeel Ali Kittaneh.pdf
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Description
A Master of Science thesis in Mathematics by Hadeel Ali Kittaneh entitled, “Threshold Functions for Modeling Gene Regulatory Networks”, submitted in June 2024. Thesis advisor is Dr. Abdul Salam Jarrah. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).
Abstract
In this thesis, we explore the properties of threshold functions with a unique updating rule and their relevance to gene regulatory models. We conduct a comparative analysis between Threshold Boolean Networks (TBNs) and Random Boolean Networks, focusing on variations in the number of inputs per gene. This analysis helps us understand how input connectivity influences network stability and phase transitions. We also investigate the dynamics and robustness of TBNs, emphasizing fixed interaction rules characteristic of genetic systems, unlike previous studies that use annealed approximations. Furthermore, we propose a new approach to assess the robustness of these networks, addressing the issue of multiple attractors in threshold Boolean networks. Our findings enhance the understanding of threshold Boolean functions and their applications in modeling gene regulatory networks.