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Published July 2007 | Published
Book Section - Chapter Open

A Multi-Model Approach to Identification of Biosynthetic Pathways

Abstract

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.

Additional Information

© 2007 IEEE. Issue Date: 9-13 July 2007; Date of Current Version: 30 July 2007. Research supported in part by the Institute for Collaborative Biotechnologies through grant DAAD19-03-D-0004 from the U.S. Army Research Office.

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Published - Dunlop2007p86802009_American_Control_Conference_Vols_1-9.pdf

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Created:
August 19, 2023
Modified:
October 20, 2023