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Fifth International Conference on Hybrid Intelligent Systems (HIS'05)
Hybrid Metabolic Flux Analysis/Artificial Neural Network Modeling of Bioprocesses
Rio de Janeiro, Brazil
December 06-December 09
ISBN: 0-7695-2457-5
ASCII Text
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Ana Teixeira, Paula M. Alves, Rui Oliveira, Carlos Alves, Manuel J. T Carrondo, "Hybrid Metabolic Flux Analysis/Artificial Neural Network Modeling of Bioprocesses," Hybrid Intelligent Systems, International Conference on, pp. 411-416, Fifth International Conference on Hybrid Intelligent Systems (HIS'05), 2005.
 
 
BibTex
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@article{ 10.1109/ICHIS.2005.59,
author = {Ana Teixeira and Paula M. Alves and Rui Oliveira and Carlos Alves and Manuel J. T Carrondo},
title = {Hybrid Metabolic Flux Analysis/Artificial Neural Network Modeling of Bioprocesses},
journal ={Hybrid Intelligent Systems, International Conference on},
volume = {0},
year = {2005},
isbn = {0-7695-2457-5},
pages = {411-416},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICHIS.2005.59},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Hybrid Intelligent Systems, International Conference on
TI - Hybrid Metabolic Flux Analysis/Artificial Neural Network Modeling of Bioprocesses
SN - 0-7695-2457-5
SP411
EP416
A1 - Ana Teixeira,
A1 - Paula M. Alves,
A1 - Rui Oliveira,
A1 - Carlos Alves,
A1 - Manuel J. T Carrondo,
PY - 2005
KW - null
VL - 0
JA - Hybrid Intelligent Systems, International Conference on
ER -
 
Ana Teixeira, Universidade Nova de Lisboa, Portugal
Paula M. Alves, Instituto de Biologia Experimental e Tecnologica, Portugal
Rui Oliveira, Universidade Nova de Lisboa, Portugal
Carlos Alves, Universidade Nova de Lisboa, Caparica, Portugal
Manuel J. T Carrondo, Instituto de Biologia Experimental e Tecnologica
The main aim of this study is to develop a bioprocess dynamic optimisation method that integrates bioreactor transport phenomena, with metabolic flux analysis (MFA). The central metabolic pathways of many biological systems with industrial interest are currently known. Bioreactor dynamic optimisation schemes could profit from the incorporation of this knowledge. A hybrid modelling methodology is presented that integrates the aforementioned concepts. The technique was successfully validated with data of a recombinant Baby Hamster Kidney (BHK-21) culture. The method allowed to identify the time evolution of intracellular metabolic fluxes and to relate this knowledge with bioreactor decision variables.
Citation:
Ana Teixeira, Paula M. Alves, Rui Oliveira, Carlos Alves, Manuel J. T Carrondo, "Hybrid Metabolic Flux Analysis/Artificial Neural Network Modeling of Bioprocesses," his, pp.411-416, Fifth International Conference on Hybrid Intelligent Systems (HIS'05), 2005
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