杂合基因算法在酵母中间代谢途径代谢通量分析中的应用

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杂合基因算法在酵母中间代谢途径代谢通量分析中的应用

张慧敏^a,b; 姚善泾^a

^a Department of Chemical and Biochemical Engineering, Zhejiang University, Hangzhou 310027, China
^b Chemical Engineering Department, Jiaxing University, Jiaxing 314000, China

收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2007-04-28 发布日期:2007-04-28
通讯作者: 张慧敏

Simulation of flux distribution in central metabolism of Saccharomyces cerevisiae by
hybridized genetic algorithm

ZHANGHuimin^a,b; YAOShanjing^a

^aDepartment of Chemical and Biochemical Engineering, Zhejiang University, Hangzhou 310027, China
^b Chemical Engineering Department, Jiaxing University, Jiaxing 314000, China

Received:1900-01-01 Revised:1900-01-01 Online:2007-04-28 Published:2007-04-28
Contact: ZHANG Huimin

摘要/Abstract

摘要： A scheme of investigating the intracellular metabolic fluxes in central metabolism of Saccharomyces cerevisiae based on isotope model and tracer experiment was developed. The metabolic model applied in this study includes the Embden-Meyerhof-Parnas pathway, the pentose phosphate pathway, the tricarboxylic acid cycle, CO2 anaplerotic reactions, ethanol and acetate formation, and pathways involved in amino acid synthesis. The approach of hybridized genetic algorithm combined with the sequential simplex technique was used to optimize a quadratic error function without the requirement of the information on the partial derivatives. The impact of some key pa-rameters on the algorithm was studied. This approach was proved to be rapid and numerically stable in the analysis of the central metabolism of S.cerevisiae.

关键词: Saccharomyces cerevisiae;metabolic flux;hybridized genetic algorithm;2D NMR;central metabolism

Abstract: A scheme of investigating the intracellular metabolic fluxes in central metabolism of Saccharomyces cerevisiae based on isotope model and tracer experiment was developed. The metabolic model applied in this study includes the Embden-Meyerhof-Parnas pathway, the pentose phosphate pathway, the tricarboxylic acid cycle, CO2 anaplerotic reactions, ethanol and acetate formation, and pathways involved in amino acid synthesis. The approach of hybridized genetic algorithm combined with the sequential simplex technique was used to optimize a quadratic error function without the requirement of the information on the partial derivatives. The impact of some key pa-rameters on the algorithm was studied. This approach was proved to be rapid and numerically stable in the analysis of the central metabolism of S.cerevisiae.

Key words: Saccharomyces cerevisiae, metabolic flux, hybridized genetic algorithm, 2D NMR, central metabolism

张慧敏, 姚善泾. 杂合基因算法在酵母中间代谢途径代谢通量分析中的应用[J]. CIESC Journal.

ZHANGHuimin, YAOShanjing. Simulation of flux distribution in central metabolism of Saccharomyces cerevisiae by
hybridized genetic algorithm[J]. .

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杂合基因算法在酵母中间代谢途径代谢通量分析中的应用

Simulation of flux distribution in central metabolism of Saccharomyces cerevisiae by
hybridized genetic algorithm

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杂合基因算法在酵母中间代谢途径代谢通量分析中的应用

Simulation of flux distribution in central metabolism of Saccharomyces cerevisiae by hybridized genetic algorithm

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Simulation of flux distribution in central metabolism of Saccharomyces cerevisiae by
hybridized genetic algorithm