]> 2026-09-04T23:49:27+00:00 A Multi-Model Approach to Identification of Biosynthetic Pathways 0 en We present an identification framework for biochemical systems that allows multiple candidate models to be compared. This framework is designed to select a model that fits the data while maintaining model simplicity. The model identification task is divided into a parameter estimation stage and a model comparison stage. Model selection is based on calculating Akaike's Information Criterion, which is a systematic method for determining the model that best represents a set of experimental data. Two case studies are presented: a simulated transcriptional control circuit and a system of oscillators that has been built and characterized in vitro. In both examples the multi-model framework is able to discriminate between model candidates to select the one that best describes the data. Mary J Dunlop, Elisa Franco, Richard M Murray 2006x American Control Conference (ACC) dfm07-acc Preprint 2016-05-15T06:17:26Z 2457523.7621065 A Multi-Model Approach to Identification of Biosynthetic Pathways Title 102 en Title