Identifiability and Indistinguishability of Linear Compartmental Models

2024. 02. 13. 17:15
Nicolette Meshkat

Joint work with Anne Shiu.

Abstract: An important question that arises when modeling is if the unknown parameters can be determined from data, the parameter estimation problem.  A key first step is to ask which parameters can be determined given perfect data.  This is called the structural identifiability problem.  We examine this question for a class of models called linear compartmental models, used in pharmacokinetics, physiology, cell biology, toxicology, and ecology.  We also examine a related problem called indistinguishability, which examines if two distinct models yield the same dynamics.  We will consider the underlying graph corresponding to our model and use tools from graph theory and computational algebra to analyze our models. 

Zoom link is available from the organizer of the seminar. Please contact János Tóth at jtoth(at)