Genome-scale network modeling

Abstract

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.