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BioMet Toolbox: genome-wide analysis of metabolism
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 mo...
Autores principales: | , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2010
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2896146/ https://www.ncbi.nlm.nih.gov/pubmed/20483918 http://dx.doi.org/10.1093/nar/gkq404 |
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author | Cvijovic, Marija Olivares-Hernández, Roberto Agren, Rasmus Dahr, Niklas Vongsangnak, Wanwipa Nookaew, Intawat Patil, Kiran Raosaheb Nielsen, Jens |
author_facet | Cvijovic, Marija Olivares-Hernández, Roberto Agren, Rasmus Dahr, Niklas Vongsangnak, Wanwipa Nookaew, Intawat Patil, Kiran Raosaheb Nielsen, Jens |
author_sort | Cvijovic, Marija |
collection | PubMed |
description | 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/. |
format | Text |
id | pubmed-2896146 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-28961462010-07-02 BioMet Toolbox: genome-wide analysis of metabolism Cvijovic, Marija Olivares-Hernández, Roberto Agren, Rasmus Dahr, Niklas Vongsangnak, Wanwipa Nookaew, Intawat Patil, Kiran Raosaheb Nielsen, Jens Nucleic Acids Res Articles 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/. Oxford University Press 2010-07-01 2010-05-18 /pmc/articles/PMC2896146/ /pubmed/20483918 http://dx.doi.org/10.1093/nar/gkq404 Text en © The Author(s) 2010. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/2.5 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.5), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Articles Cvijovic, Marija Olivares-Hernández, Roberto Agren, Rasmus Dahr, Niklas Vongsangnak, Wanwipa Nookaew, Intawat Patil, Kiran Raosaheb Nielsen, Jens BioMet Toolbox: genome-wide analysis of metabolism |
title | BioMet Toolbox: genome-wide analysis of metabolism |
title_full | BioMet Toolbox: genome-wide analysis of metabolism |
title_fullStr | BioMet Toolbox: genome-wide analysis of metabolism |
title_full_unstemmed | BioMet Toolbox: genome-wide analysis of metabolism |
title_short | BioMet Toolbox: genome-wide analysis of metabolism |
title_sort | biomet toolbox: genome-wide analysis of metabolism |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2896146/ https://www.ncbi.nlm.nih.gov/pubmed/20483918 http://dx.doi.org/10.1093/nar/gkq404 |
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