Mathematical Biology

Multi-Scale Models of Infectious Disease Dynamics and Validating with Data The bidirectional feedback induced through population and individual-level infectious disease and host immune dynamics requires development of innovative multi-scale models. In this talk, I will introduce structured nonlinear partial differential equation models linking immunology and epidemiology, along with novel stability analysis and computational tools for …

Modelling Microtube Driven Invasion of Glioma Malignant gliomas are highly invasive brain tumors. Recent attention has focused on their capacity for network-driven invasion, whereby mitotic events can be followed by the migration of nuclei along long thin cellular protrusions, termed tumour microtubes (TM). Here I develop a mathematical model that describes this microtube-driven invasion of …

Modeling the effects of Aedes aegypti's larval environment on population and disease spread Mosquitoes vector harmful pathogens that infect millions of people every year, and developing approaches to effectively control mosquitoes is a topic of great interest. However, the success of many control measures is highly dependent upon ecological, physiological, and life history traits of …

Modeling Mesenchymal Cell Motion - Force, Speed and the Role of Focal Adhesion Lifetimes In this talk I will present a force based mathematical model of mesenchymal cell motion where adhesion sites are randomly placed and have a probabilistically determined lifespan. Numerical simulations and theoretical results will be discussed and compared to experimental data. The …

Tumor Composition and the Host Environment on Cancer Treatment Strategies The one-size-fits-all approach is not effective at treating cancer and tumor heterogeneity plays an important role in patient response. Current dogma characterizes tumor heterogeneity resulting from compounding genetic and epigenetic changes and instability, ultimately driving unfavorable outcomes for these patients. However, some cancers, including many …

Estimating the Long-term Behavior of Biologically Inspired Agent-based Models An agent-based model (ABM) is a computational model in which the local interactions of autonomous agents with each other and with their environment give rise to global properties within a given domain. The use of ABMs in biology has become widespread over the last few years …

Challenges and Opportunities for Translational Research: The Power of Data Integration With increased regulatory burden and high expectations from prescribers and patients, it is no longer cost- nor time-effective to tackle all open questions experimentally. As a result, an increasing number of decisions is informed by modeling and simulation approaches, which integrate all available knowledge …