원문정보
초록
영어
The advent of in silico genome-scale model developed various algorithms to apply to the development of strain for biochemical production. Flux balance analysis (FBA) optimizes a specific objective function by linear programming under pseudo-steady state based on the stoichiometry of metabolic reactions. In order to incorporate the physiological characteristics of the organisms under gene knock-out conditions, algorithms such as minimization of metabolic adjustment (MOMA) and regulatory on/off minimization (ROOM) were developed. However,
to improve a strain for biochemical production, the organism should be investigated from diverse sides simultaneously: for instance, biomass formation, biochemical production, and waste formation. In this respect, we propose a new approach called the Flux Scanning with Compromised Objective Fluxes (FSCOF), multi-objective algorithm. [This work was supported by Korean Systems Biology Research program (M10309020000-03B5002-00000) of the Ministry of Education, Science and Technology. Further supports by LG Chem Chair Professorship,
Microsoft and IBM SUR program are appreciated.]