Modeling and Simulation of Discrete Event Dynamic System with Reference to Biological Pathways

Abstract

This thesis presents a comprehensive framework for modeling newlinemetabolic pathways in Mycobacterium tuberculosis (Mtb) through newlinethe lens of Discrete Event Dynamic Systems (DEDS). Recognizing newlinethe limitations of traditional differential equation models in capturing newlineasynchronous and event-driven biological behaviors, this newlinestudy uses Petri nets to offer a precise representation of metabolic newlineinteractions. These networks naturally accommodate concurrency, newlinesynchronization, and discrete transitions, making them well-suited newlinefor biological systems analysis. newlineThe core objective is to identify the potential drug targets and newlineanalyze key metabolic subsystems of Mtb, particularly pyruvate newlinemetabolism, coenzyme A, and UDP-N-acetylglucosamine biosynthesis, newlineunder varied regulatory and environmental conditions. Using newlinemodeling tools such as Snoopy and COPASI and databases such newlineas KEGG, MetaCyc, and BioCyc, the research integrates discrete newlinemodeling with rich bioinformatics data. This approach enables simulation newlineof molecular processes with a focus on robustness, system newlinestability, and metabolic response to perturbations. newlineThe methodological foundation includes Petri Nets. These extensions newlinefacilitate modeling of temporal delays, molecular heterogeneity, newlineand probabilistic transitions, enriching the biological realism of newlinethe system. Key techniques such as invariant analysis and reachability newlinetesting ensure the biological precision and feasibility of the newlinevi newlinepathway. newlineThis thesis delivers contributions in two main areas newline