TAILIEUCHUNG - Báo cáo khoa học: Reduction of a biochemical model with preservation of its basic dynamic properties

The complexity of full-scale metabolic models is a major obstacle for their effective use in computational systems biology. The aim of model reduction is to circumvent this problem by eliminating parts of a model that are unimportant for the properties of interest. | ễFEBS Journal Reduction of a biochemical model with preservation of its basic dynamic properties Sune Dan01 Mads F. Madsen1 Henning Schmidt2 and Gunnar Cedersund2 1 Department of MedicalBiochemistry and Genetics University of Copenhagen Denmark 2 Fraunhofer Chalmers Research Centre for IndustrialMathematics Gothenburg Sweden Keywords core model glycolysis Hopf bifurcation model optimization model reduction Correspondence H. Schmidt Fraunhofer Chalmers Research Centre for IndustrialMathematics Sven Hultins gata 9D S-41288 Gothenburg Sweden E-mail henning@ Note The mathematicalmodels described here have been submitted to the Online Cellular Systems Modelling Database and can be accessed free of charge at http . database hynne http database dano1 http database dano2 http jjj. database dano3 index. html Received 8 June 2006 revised 22 August 2006 accepted 31 August 2006 The complexity of full-scale metabolic models is a major obstacle for their effective use in computational systems biology. The aim of model reduction is to circumvent this problem by eliminating parts of a model that are unimportant for the properties of interest. The choice of reduction method is influenced both by the type of model complexity and by the objective of the reduction therefore no single method is superior in all cases. In this study we present a comparative study of two different methods applied to a 20D model of yeast glycolytic oscillations. Our objective is to obtain biochemically meaningful reduced models which reproduce the dynamic properties of the 20D model. The first method uses lumping and subsequent constrained parameter optimization. The second method is a novel approach that eliminates variables not essential for the dynamics. The applications of the two methods result in models of eight lumping six elimination and three lumping followed by .

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