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基元通量模式预测酵母生长现象

Prediction of Saccharomyces Cerevisiae Growth Phenotypes Based on Elementary Flux Mode Analysis

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【作者】 蒋达王永华李燕张述伟杨胜利杨凌

【Author】 JIANG Da~ 1 , WANG Yong-Hua~ 2 , LI Yan~ 1 , ZHANG Shu-Wei~ 1 , YANG Sheng-Li~ 2 , YANG Ling~ 2 (1. Department of Chemical Engineering, Dalian University of Technology, Dalian 116012, China; 2. Lab of Pharmaceutical Resource Discovery, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China)

【机构】 大连理工大学化学工程系中国科学院大连化学物理研究所中国科学院大连化学物理研究所 大连116012药用资源开发研究组大连116023大连116012

【Abstract】 The purpose of this work is to illustrate the relationship between genotype and phenotype in the complex cellular network of saccharomyces cerevisiae. As a structure-oriented method, using elementary flux mode(EFM) analysis can obtain its popularity in analysis of the robustness of the central metabolism, as well as network function of some organisms. However, this method has not been widely used for modeling gene deletion phenotype. By enumerating all the metabolic pathways, the EFM analysis presented herein can be used to identify the functional features and predict the growth phenotype of the S.cerevisiae. In comparison with the flux balance analysis(FBA), the performance of EFM analysis was superior to FBA in prediction of gene deletion phenotype. EFM analysis is demonstrated to be an effective tool for bridging the gap between metabolic network and growth phenotype.

【基金】 国家“九七三”前沿专项计划(批准号:2003CCA03400);国家“八六三”计划(批准号:2003AA223061)资助
  • 【文献出处】 高等学校化学学报 ,Chemical Journal of Chinese Universities , 编辑部邮箱 ,2006年09期
  • 【分类号】Q935-3
  • 【被引频次】1
  • 【下载频次】126
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