Genome-Scale Network Modeling

  • Sang Yup Lee
  • Seung Bum Sohn
  • Hyun Uk Kim
  • Jong Myoung Park
  • Tae Yong Kim
  • Jeffrey D. Orth
  • Bernhard Ø. Palsson


Genome-scale models have garnered considerable interest for their ability to elucidate cellular characteristics and lead to a better understanding of biological systems. Metabolic models in particular have been widely used to study complex metabolic pathways in order to better understand microbial systems and to design strategies for engineering various biotechnological applications. Similar to metabolic networks, transcriptional and signaling network models have also been reconstructed to elucidate regulatory interactions and to further understand the response of systems to various environmental stimuli. However, a true genome-scale model that integrates all these characteristics into one comprehensive model has not yet been constructed. For the time being, the existing network models have individually contributed to the knowledge of their respective fields and to our understanding of biological systems. In selected cases they have provided design strategies for systems wide engineering of metabolism. There have been several attempts to integrate these networks to realize the full potential of a complete cellular network model, although there is still room for further development. Here, we review the different network types and highlight their contributions to biotechnological applications via illustrative examples.


Genome-scale model Metabolic network Transcriptional network Signaling network Escherichia coli Network reconstruction Genome annotation In silico Stoichiometric matrix Steady-state Automatic reconstruction Single-input module Top-down Bottom-up Boolean formalism Flux analysis Stoichiometric formalism Kinetic formalism 



This work was supported by the Intelligent Synthetic Biology Center (2011-0031963) through the Global Frontier Project of Ministry of Education, Science and Technology.


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Copyright information

© Springer Science+Business Media Dordrecht 2012

Authors and Affiliations

  • Sang Yup Lee
    • 1
  • Seung Bum Sohn
    • 1
    • 2
  • Hyun Uk Kim
    • 2
  • Jong Myoung Park
    • 1
    • 2
  • Tae Yong Kim
    • 2
  • Jeffrey D. Orth
    • 3
  • Bernhard Ø. Palsson
    • 3
  1. 1.Metabolic and Biomolecular Engineering National Research Laboratory, Department of Chemical and Biomolecular Engineering (BK21 Program), Center for Systems and Synthetic BiotechnologyInstitute for the BioCentury, KAISTDaejeonRepublic of Korea
  2. 2.Bioinformatics Research Center, KAISTDaejeonRepublic of Korea
  3. 3.Department of BioengineeringUniversity of California, San DiegoLa JollaUSA

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