(A) computational framework using microbial adaptation mechanisms for the redesign of metabolic network = 미생물 환경적응 기작을 응용한 대사 네트워크 재설계를 위한 계산적 프레임워크

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Genome-scale stoichiometric models are useful predictive tools for redesigning metabolic networks. However, the high computational cost of identifying appropriate metabolic engineering strategies restricts the applicability of computational models to the optimization with a limited number of modifications. By mimicking adaptation phenomena in nature, we developed a novel optimization framework named EvoKO that can find optimal knockout strategies with an unlimited number of knockouts. EvoKO was successfully applied to the identification of an optimal metabolic engineering strategy for the production of hydrogen using $\it{Escherichia coli}$. The predicted hydrogen yield of the mutant suggested by EvoKO was about 77.4% of the theoretical maximum, which is about two-fold higher than those suggested using previous optimization frameworks.
Advisors
Kim, Sun-Changresearcher김선창researcher
Description
한국과학기술원 : 생명과학과,
Publisher
한국과학기술원
Issue Date
2010
Identifier
455362/325007  / 020035246
Language
eng
Description

학위논문(박사) - 한국과학기술원 : 생명과학과, 2010.08, [ iv, 85 p. ]

Keywords

Optimization; Adaptation; Metabolism; 대사네트워크; 최적화; 적응

URI
http://hdl.handle.net/10203/27711
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=455362&flag=dissertation
Appears in Collection
BS-Theses_Ph.D.(박사논문)
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