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In this article, we introduce the new approach "fluorescence grid basedaggregation (FGBA)" to justify a dynamical model of protein expression usingexperimental fluorescence histograms. In this approach, first, we describe thedynamics of the gene-protein system by a chemical master equation (CME), whilethe protein production rates are unknown. Then, we aggregate the states of theCME into unknown group sizes. We show that these unknown values can be replacedby the data from the experimental fluorescence histograms. Consequently, finalprobability distributions correspond to the experimental fluorescencehistograms.

Flow Cytometry Based State Aggregation of a Stochastic Model of Protein Expression