**Additional authors**: Megan Greischar, Department of Ecology and Evolutionary Biology, Cornell University; Nicole Mideo, Department of Ecology and Evolutionary Biology, University of Toronto

MS07 -
MEPI-1

Cartoon Room 1 (#3145) in The Ohio Union

# Recent advances in parameter identifiability of mathematical models in mathematical biology

#### Thursday, July 20 at 04:00pm

Room assignment: Cartoon Room 1 (#3145) in The Ohio Union.

**MS06-MEPI-1**(click here).

**Organizers:**

#### Omar Saucedo, Bren Case, Lauren Childs

**Description**:

Parameter estimation is common practice when determining unknown parameters of a mathematical model. However, whether estimated parameters are reliable depends on the quantity and quality of available data, as well as the complexity of the model. Although models in mathematical biology tend to be highly nonlinear and can interact with data in unexpected ways, identifiability is rarely assessed prior to model fitting. Identifiability analysis comes in two flavors, the first focusing on whether there exists a unique set of parameters for all possible model output, and the second focusing the set of plausible parameters inferred from noisy data. Both approaches employ a range of geometric and statistical techniques. The goal of this mini-symposium is to bring in experts working throughout the immense field of mathematical biology to discuss the most recent advancements in identifiability.

#### Madeline A. E. Peters

*Michigan State University (Microbiology and Molecular Genetics)*

###### "Challenges in forming inferences from limited data: a case study of malaria parasite maturation"

#### Bren Case

*University of Vermont (Computer Science)*

###### "Restricted Marginal Divergence: an efficient Bayesian measure of practical identifiability for nonlinear systems in biology and epidemiology"

**Additional authors**: Jean-Gabriel Young, Department of Mathematics & Statistics, University of Vermont; Laurent Hébert-Dufresne, Department of Computer Science, University of Vermont