BioMet Toolbox: genome-wide analysis of metabolism
Journal article, 2010

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/.

transcriptional regulation

network

reconstruction

saccharomyces-cerevisiae

fluxes

models

systems biology

Author

Marija Cvijovic

Chalmers, Chemical and Biological Engineering, Life Sciences, System Biology

Roberto Olivares Hernandez

Chalmers, Chemical and Biological Engineering, Life Sciences, System Biology

Rasmus Ågren

Chalmers, Chemical and Biological Engineering, Life Sciences, System Biology

Niklas Dahr

Chalmers, Chemical and Biological Engineering

Wanwipa Vongsangnak

Chalmers, Chemical and Biological Engineering, Life Sciences, System Biology

Intawat Nookaew

Chalmers, Chemical and Biological Engineering, Life Sciences, System Biology

K. R. Patil

Technical University of Denmark (DTU)

Jens B Nielsen

Chalmers, Chemical and Biological Engineering, Life Sciences, System Biology

Nucleic Acids Research

0305-1048 (ISSN) 1362-4962 (eISSN)

Vol. 38 SUPPL. 2 W144-W149 gkq404

Areas of Advance

Information and Communication Technology

Life Science Engineering (2010-2018)

Subject Categories

Industrial Biotechnology

DOI

10.1093/nar/gkq404

More information

Latest update

2/28/2018