title: Systems biotechnology for strain improvement.
abstract: Various high-throughput experimental techniques are routinely used for generating large amounts of omics data. In parallel, in silico modelling and simulation approaches are being developed for quantitatively analyzing cellular metabolism at the systems level. Thus informative high-throughput analysis and predictive computational modelling or simulation can be combined to generate new knowledge through iterative modification of an in silico model and experimental design. On the basis of such global cellular information we can design cells that have improved metabolic properties for industrial applications. This article highlights the recent developments in these systems approaches, which we call systems biotechnology, and discusses future prospects.
authors.affiliation: Metabolic and Biomolecular Engineering National Research Laboratory and Department of Chemical and Biomolecular Engineering, Korea Advanced Institute of Science and Technology, 373-1 Guseong-dong, Yuseong-gu, Daejeon 305-701, Korea. leesy@kaist.ac.kr
authors.forename: Sang Yup
authors.initials: SY
authors.lastname: Lee
authors.forename: Dong-Yup
authors.initials: DY
authors.lastname: Lee
authors.forename: Tae Yong
authors.initials: TY
authors.lastname: Kim
mesh_terms: D016678:Genome; D023281:Genomics / Q000379:methods*; D007218:Industrial Microbiology / Q000379:methods* / Q000639:trends; D008962:Models, Theoretical; D040901:Proteomics / Q000379:methods*