Weber, Lisa, authorRaymond, Will, authorMunsky, Brian, author2017-11-132017-11-132017https://hdl.handle.net/10217/184929In quantitative biology, one may use many different model scales or approaches to match models to experimental data. We use a simplified gene regulation model with a time-dependent input signal to illustrate many concepts, including ODE analyses of deterministic processes; chemical master equation and finite-state projection analyses of heterogeneous processes; and stochastic simulations. We consider several model hypotheses and simulated single-cell data to illustrate mechanism and parameter identification as precisely as possible, while exploring how approach or experiment design affect parameter uncertainty. Our approach is based upon previous investigations to explore signal-activated gene expression models in yeast and human cells.born digitalStudent workspostersengCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.gene regulationparameter identificationfinite state projectionpredictive modelingparameter uncertaintyText