Extend structural indistinguishability theory to nonlinear systems and incorporate data effects

Develop structural indistinguishability results applicable to nonlinear dynamical systems, such as Hill-function-based ODE gene regulatory models, and incorporate the influence of experimental data on indistinguishability analyses.

Background

Current theoretical results on structural indistinguishability largely pertain to linear systems and do not consider how experimental data quality and sampling affect the ability to distinguish models.

The models studied in this paper are nonlinear and data-limited, underscoring the need for theory that accommodates nonlinearity and data dependence to better interpret practical indistinguishability findings.