Using Sensitivity Analysis and Uncertainty Quantification to Develop or Improve Biomathematical Models

Organizers:

Kelsey Gasior (University of Notre Dame)

Description:

Developing biomathematical models creates a paradox when determining how best to capture a system’s behavior. Too little information creates uninformative models while too many terms results in overparameterization. Further complications occur with the inclusion of measured, experimental data. Understanding the data presented, as well as the model constructed, means that we need to balance the complexity of the model with the information content in the data. In these situations, we often turn to sensitivity analysis. Sensitivity analysis is an important tool when faced with the inability to uniquely determine parameters from existing datasets, known as parameter identifiability. Additionally, it can help us identify the most influential parameters, test the robustness of our models, and improve our understanding of the system’s behavior. The work presented in this minisymposium will discuss the use of novel methodologies in sensitivity analysis and uncertainty quantification to develop biologically relevant biomathematical models. While the biological applications include epithelial intracellular dynamics, bacterial persistence, ecology, and epidemiology, this session aims to connect researchers interested in parameter estimation, sensitivity analysis, and uncertainty quantification. Discussing the development and relevance of these tools on different biological topics will ultimately spark conversations about the needs and future directions for method development.

Diversity Statement:

This session connects researchers interested in sensitivity analysis and uncertainty quantification and, as such, brings together a diverse group of researchers. Researchers in this session span different biological interests, career levels, and genders and can provide excellent insight into the use of analytical techniques in different biological contexts. Further, the organizer is committed to always encouraging and promoting diversity at SMB and in the biomathematical community in general.