For more information about this meeting, contact Becky Halpenny.
|Title:||"Dynamic Modeling of Biological and Physical Systems"|
|Seminar:||Ph.D. Thesis Defense|
|Speaker:||Assieh Saadatpour Moghaddam, Advisers: Mark Levi (Math) & Reka Albert (Physics), Penn State|
|Given the complexity and interactive nature of many biological and physical systems, constructing informative and coherent network models of these systems and subsequently developing efficient approaches to analyze the models is of utmost importance. The combination of network modeling and dynamic analysis enables one to investigate the behavior of the underlying system as a whole and to make experimentally testable predictions about less-understood aspects of the processes involved. This dissertation reports on a combination of theoretical and computational approaches for network-based dynamic analysis of several highly interactive biological and physical systems. Various dynamic modeling approaches, ranging from Boolean to continuous models, are employed to carry out a systematic analysis of the long-term behavior (attractors) of the respective systems. First, we employ a Boolean dynamic framework to model two biological systems: the abscisic acid (ABA) signal transduction network in plants and the T-LGL leukemia signaling network in humans. Given the relatively large number of components in these networks, we develop a network reduction technique leading to a significant decrease in the computational burden associated with the state space analysis of Boolean models while preserving essential dynamical features. For the ABA system, we utilize a synchronous and three different asynchronous Boolean dynamic methods and compare the attractors of the system and their basins of attraction for both unperturbed and perturbed systems. For the T-LGL signaling network, the best-performing asynchronous Boolean dynamic method identified in our first study is used to identify the disease states of the components of the system and to propose several novel candidate therapeutic targets. Next, we apply a Boolean-continuous hybrid (piecewise linear) dynamic formalism to model a pathogen-immune system interaction network, and present the results of a comparative study of the dynamic characteristics of Boolean and hybrid models. Finally, we rely on continuous dynamic modeling to prove the existence of traveling wave solutions in a better-characterized physical system, namely, a lattice of coupled pendula in the presence of damping and forcing. The theoretical and computational approaches developed in this dissertation provide a bird’s-eye-view of the avenues available for model-driven analysis of complex biological and physical systems.|
Room Reservation Information
|Date:||05 / 10 / 2012|
|Time:||08:00am - 10:00am|