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Abstract

Metabolic engineering allows purposeful modification of metabolic and cellular network towards achieving several goals including enhanced production of various bioproducts, production of novel products, and broadening the substrate utilization range. Traditional metabolic engineering has been performed by manipulating a handful of genes and pathways based on known literature information and our rational thinking. Advances in omics technology, computational bioscience, and systems biology are now providing us with new information and knowledge that had not been possible to obtain using traditional approaches. Systems biology is allowing us to elucidate the metabolism and physiology of cells and organisms at the global levels. Metabolic engineering based on the systems-level analysis of cells and organisms, termed systems metabolic engineering, is now offering a new powerful way of designing and developing strains having improved performance. In this lecture, I will present the general strategies of systems metabolic engineering. Also, several examples of applying systems metabolic engineering for the production of amino acids, primary metabolite (succinic acid) and secondary metabolite (lycopene) will be presented.

About the keynote speaker. Dr. Sang Yup Lee is Distinguished Professor and LG Chem Chair Professor at the Department of Chemical and Biomolecular Engineering, KAIST, Korea. He is also the Director of Center for Systems and Synthetic Biotechnology, Director of BioProcess Engineering Research Center, Director of Bioinformatics Research Center, and Co-Director of the Institute for the BioCentury. He has published more than 230 journal papers, 40 books/book chapters, 270 patents, and presented more than 900 papers at conferences. He is currently serving as Senior Editor, Editor, Associate Editor, or Board Member of 12 journals including Biotechnology and Bioengineering.

Keywords

System Biology Succinic Acid Cellular Network Metabolic Engineering Primary Metabolite 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Sang Yup Lee
    • 1
  1. 1.Korea Advanced Institute of Science and TechnologyDaejeon

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