基元通量模式预测酵母生长现象

作     者：蒋达 王永华 李燕 张述伟 杨胜利 杨凌 JIANG Da;WANG Yong-Hua;LI Yan;ZHANG Shu-Wei;YANG Sheng-Li;YANG Ling

作者机构：大连理工大学化学工程系大连116012 中国科学院大连化学物理研究所药用资源开发研究组大连116023 

出 版 物：《高等学校化学学报》 (Chemical Journal of Chinese Universities)

年 卷 期：2006年第27卷第9期

页      面：1683-1685页

核心收录：

学科分类：0831[工学-生物医学工程（可授工学、理学、医学学位）] 0711[理学-系统科学] 081704[工学-应用化学] 07[理学] 08[工学] 0817[工学-化学工程与技术] 070303[理学-有机化学] 0703[理学-化学] 

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 

主　　题：预测 基元通量模式 啤酒酵母 生长现象 

摘      要：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 ***. 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.