A Systems Approach to Modeling and Simulating Cellular Stochasticity and Adaptation
Friday, May 4, 2018
1:00 PM-3:00 PM
BIOMED PhD Thesis Defense
A Systems Approach to Modeling and Simulating Cellular Stochasticity and Adaptation Across Multiple Biological Scales
Justin Melunis, PhD Candidate, School of Biomedical Engineering, Science and Health Systems, Drexel University
Uri Hershberg, PhD, Associate Professor, School of Biomedical Engineering, Science and Health Systems, Drexel University
To understand the behavior of biological systems we need to consider that they are made of populations of individual cells. The behavior of these cells is also dependent on the interactions of multiple organelles and protein complexes. Every response is dependent on interactions of cells across multiple scales from the molecular through the level of the organelle, the cell and then to cell-cell interactions. To look at these cells across different biological scales, with a systems approach, we need to develop mathematical models and simulations that allow us to consider biological interactions at different scales and across scales.
Creating such multi-scale models of organelle and cellular dynamics was the heart of my thesis. To do so I pursued 3 aims:
1) I conducted statistical and model-based analysis of imaging experiments at both the cellular and organelle biological scales
2) I developed TIPS, a stochastic modeling framework for tracking of individual agent kinematics through complex binding to model and simulate cellular behavior at the molecular scale. I applied TIPS to simulate Calcium dependent STIM and Orai binding and motion.
3) I developed MiGHT a multi-scalar stochastic modeling framework for the simulation of cellular adaptation and utilized this framework to model the interconnected networks of cellular behavior across multiple biological scales.
I used MiGHT to model and simulate the macrophage response to lipopolysaccharide, specifically modeling how the macrophage response adapts to the cytokine environment through the modeling of cellular behavior across the molecular, cellular, and systemic biological scales. Here, my thesis provided a way to approach taking experimental data to single scale models and simulations to interconnected multi-scalar models and simulations. In doing so, this work has provided a way in which we can model and simulate how perturbations at molecular scales, such as genetic alterations or drug administration, can impact cellular and systemic behavior.