Mini-symposium (MS)

MS8: Modeling and Data Science in Quantitative Biology: Predictions and Descriptions

Organizers: Bhargav Karamched, Florida State University

Abstract: Biological processes are incredibly complex, posing a plethora of challenges that obfuscate underlying mechanisms and render outcomes unpredictable. For example: How do bacteria coordinate activity across large spatial domains that exceed the correlation lengths of their communication signals? How do vesicles reach specific locations in a cell in a timely fashion? What are optimal methods to prevent spread of disease? Obtaining answers to such questions via experimental methods often requires significant time and money. Hence, there is a growing need for theoretical investigation to guide experimentalists with predictions and uncover underlying mechanisms. Theoretical models have a longstanding tradition of capturing fundamental dynamics of biological processes. Moreover, the emergence of data science and machine learning as powerful tools to match theoretical models to data has improved theoretical models' predictive power. Thus, modeling and data science together are valuable for improving understanding in biological science. This mini-symposium will feature talks by young academics on how theoretical models of different areas in biology uncover underlying mechanisms and how machine learning and data science have helped make novel, sometimes counterintuitive, predictions.

Saturday, September 18, 10:00 AM – 12:00 PM: Part I of II

Room: Libry 3041

10:00 – 10:30 Bhargav Karamched, Florida State University, Delay-induced uncertainty in a paradigmatic glucose-insulin model

10:30 – 11:00 George Lytle, University of Montevallo, Management strategies using optimal control for disease outbreaks

11:00 – 11:30 Elizabeth Cherry, Georgia Institute of Technology, Data-driven approaches for predicting and reconstructing cardiac electrical dynamics

11:30 – 12:00 Mehran Fazli, Florida State University, Fast-slow analysis of a stochastic mechanism for electrical bursting

Saturday, September 18, 3:30 PM – 5:30 PM: Part II of II

Room: Libry 3041

3:30 – 4:00 Casian Pantea,West Virginia University, Cyclic network structure and multistationarity in biochemical networks

4:00 – 4:30 Veronica Ciocanel, Duke University, Modeling and data analysis for filament organization in cells

4:30 – 5:00 Xiyuan Liu, Louisiana Tech University, Gene expression level classification using conditional random fields

5:00 – 5:30 Kellen Myers, Tusculum University, The epidemiological implications of jails for COVID-19