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BioMet Toolbox: genome-wide analysis of metabolism

Marija Cvijovic (Institutionen för kemi- och bioteknik, Systembiologi) ; Roberto Olivares Hernandez (Institutionen för kemi- och bioteknik, Systembiologi) ; Rasmus Ågren (Institutionen för kemi- och bioteknik, Systembiologi) ; Niklas Dahr (Institutionen för kemi- och bioteknik) ; Wanwipa Vongsangnak (Institutionen för kemi- och bioteknik, Systembiologi) ; Intawat Nookaew (Institutionen för kemi- och bioteknik, Systembiologi) ; K. R. Patil ; Jens B. Nielsen (Institutionen för kemi- och bioteknik, Systembiologi)
Nucleic Acids Research (0305-1048). Vol. 38 (2010), p. W144-W149.
[Artikel, refereegranskad vetenskaplig]

The rapid progress of molecular biology tools for directed genetic modifications, accurate quantitative experimental approaches, high-throughput measurements, together with development of genome sequencing has made the foundation for a new area of metabolic engineering that is driven by metabolic models. Systematic analysis of biological processes by means of modelling and simulations has made the identification of metabolic networks and prediction of metabolic capabilities under different conditions possible. For facilitating such systemic analysis, we have developed the BioMet Toolbox, a web-based resource for stoichiometric analysis and for integration of transcriptome and interactome data, thereby exploiting the capabilities of genome-scale metabolic models. The BioMet Toolbox provides an effective user-friendly way to perform linear programming simulations towards maximized or minimized growth rates, substrate uptake rates and metabolic production rates by detecting relevant fluxes, simulate single and double gene deletions or detect metabolites around which major transcriptional changes are concentrated. These tools can be used for high-throughput in silico screening and allows fully standardized simulations. Model files for various model organisms (fungi and bacteria) are included. Overall, the BioMet Toolbox serves as a valuable resource for exploring the capabilities of these metabolic networks. BioMet Toolbox is freely available at www.sysbio.se/BioMet/.

Nyckelord: saccharomyces-cerevisiae, systems biology, transcriptional regulation, network, models, reconstruction, fluxes



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Denna post skapades 2010-12-17. Senast ändrad 2014-10-27.
CPL Pubid: 131217

 

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Institutioner (Chalmers)

Institutionen för kemi- och bioteknik, Systembiologi (2008-2014)
Institutionen för kemi- och bioteknik (2005-2014)

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Informations- och kommunikationsteknik
Livsvetenskaper
Industriell bioteknik

Chalmers infrastruktur

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Systems Biology in Saccharomyces cerevisiae. Statistical data analysis and mathematical methods