Maximum entropy decomposition of flux distribution at steady state to elementary modes(BIOINFORMATICS)
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概要
- 論文の詳細を見る
Enzyme Control Flux (ECF) is a method of correlating enzyme activity and flux distribution. The advantage of ECF is that the measurement integrates proteome data with metabolic flux analysis through Elementary Modes (EMs). But there are a few methods of effectively determining the Elementary Mode Coefficient (EMC) in cases where no objective biological function is available. Therefore, we proposed a new algorithm implementing the maximum entropy principle (MEP) as an objective function for estimating the EMC. To demonstrate the feasibility of using the MEP in this way, we compared it with Linear Programming and Quadratic Programming for modeling the metabolic networks of Chinese Hamster Ovary, Escherichia coli, and Saccharomyces cerevisiae cells. The use of the MEP presents the most plausible distribution of EMCs in the absence of any biological hypotheses describing the physiological state of cells, thereby enhancing the prediction accuracy of the flux distribution in various mutants.
- 社団法人日本生物工学会の論文
著者
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Zhao Quanyu
Department of Bioscience and Bioinformatics, Kyushu Institute of Technology
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Kurata Hiroyuki
Department of Bioscience and Bioinformatics, Kyushu Institute of Technology
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Zhao Quanyu
Department Of Bioscience And Bioinformatics Kyushu Institute Of Technology
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Zhao Quanyu
Dep. Of Bioscience And Bioinformatics Kyushu Inst. Of Technol. 680-4 Kawazu Iizuka Fukuoka 820-8502
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Kurata Hiroyuki
Dep. Of Bioscience And Bioinformatics Kyushu Inst. Of Technol. 680-4 Kawazu Iizuka Fukuoka 820-8502
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Kurata Hiroyuki
Department Of Bioscience And Bioinformatics Kyushu Institute Of Technology
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