Parameter estimation in batch bioreactor simulation using metabolic models / Juha T. Leppävuori in Industrial & engineering chemistry research, Vol. 50 N° 21 (Novembre 2011)  

Public ISBD [article]  inIndustrial & engineering chemistry research > Vol. 50 N° 21 (Novembre 2011) . - pp. 12080-12091 Titre : Parameter estimation in batch bioreactor simulation using metabolic models : sequential solution with direct sensitivities Type de document : texte imprimé Auteurs : Juha T. Leppävuori, Auteur Année de publication : 2011 Article en page(s) : pp. 12080-12091 Note générale : Chimie industrielle Langues : Anglais (eng) Mots-clés : Sensitivity analysis Modeling Bioreactor Batchwise Parameter estimation Résumé : In this study, we propose a parameter estimation method for genome-scale dynamic flux balance (DFBA) models. A bilevel optimization problem is reformulated as a differential-algebraic equation (DAE) optimization problem and solved sequentially, using gradient-based optimization with direct sensitivity equations. The resulting solution method is computationally efficient for today's largest genome-scale metabolic models. The parameter estimation method combined with parameter selection algorithm is applied on simulated and experimental data. This paper presents the parameter estimation and selection method and numerical results of estimation of kinetic parameters of the DFBA model of anaerobic batch fermentation. The results show improved computational performance over previous approaches, thus making parameter estimation available for genome-scale DFBA models. DEWEY : 660 ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=24697525 [article] Parameter estimation in batch bioreactor simulation using metabolic models : sequential solution with direct sensitivities [texte imprimé] / Juha T. Leppävuori, Auteur . - 2011 . - pp. 12080-12091. Chimie industrielle Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 50 N° 21 (Novembre 2011) . - pp. 12080-12091 Mots-clés : Sensitivity analysis Modeling Bioreactor Batchwise Parameter estimation Résumé : In this study, we propose a parameter estimation method for genome-scale dynamic flux balance (DFBA) models. A bilevel optimization problem is reformulated as a differential-algebraic equation (DAE) optimization problem and solved sequentially, using gradient-based optimization with direct sensitivity equations. The resulting solution method is computationally efficient for today's largest genome-scale metabolic models. The parameter estimation method combined with parameter selection algorithm is applied on simulated and experimental data. This paper presents the parameter estimation and selection method and numerical results of estimation of kinetic parameters of the DFBA model of anaerobic batch fermentation. The results show improved computational performance over previous approaches, thus making parameter estimation available for genome-scale DFBA models. DEWEY : 660 ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=24697525

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