Analysis and Logical Modeling of Biological Signaling Transduction Networks

Open Access
Sun, Zhongyao
Graduate Program:
Doctor of Philosophy
Document Type:
Date of Defense:
Committee Members:
  • Reka Z Albert, Dissertation Advisor
  • Reka Z Albert, Committee Chair
  • Dezhe Jin, Committee Member
  • Jorge Osvaldo Sofo, Committee Member
  • John Fricks, Committee Member
  • network science
  • biological networks
  • discrete dynamics
  • Boolean network
  • system biology
  • network modeling
  • signal transduction
The study of network theory and its application span across a multitude of seemingly disparate fields of science and technology: computer science, biology, social science, linguistics, etc. It is the intrinsic similarities embedded in the entities and the way they interact with one another in these systems that link them together. In this dissertation, I present from both the aspect of theoretical analysis and the aspect of application three projects, which primarily focus on signal transduction networks in biology. In these projects, I assembled a network model through extensively perusing literature, performed model-based simulations and validation, analyzed network topology, and proposed a novel network measure. The application of network modeling to the system of stomatal opening in plants revealed a fundamental question about the process that has been left unanswered in decades. The novel measure of the redundancy of signal transduction networks with Boolean dynamics by calculating its maximum node-independent elementary signaling mode set accurately predicts the effect of single node knockout in such signaling processes. The three projects as an organic whole advance the understanding of a real system as well as the behavior of such network models, giving me an opportunity to take a glimpse at the dazzling facets of the immense world of network science.