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Radrich, K. ; Tsuruoka, Y.* ; Dobson, P.* ; Gevorgyan, A.* ; Swainston, N.* ; Baart, G.* ; Schwartz, J.M.*

Integration of metabolic databases for the reconstruction of genome-scale metabolic networks.

BMC Syst. Biol. 4:114 (2010)
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Background: Genome-scale metabolic reconstructions have been recognised as a valuable tool for a variety of applications ranging from metabolic engineering to evolutionary studies. However, the reconstruction of such networks remains an arduous process requiring a high level of human intervention. This process is further complicated by occurrences of missing or conflicting information and the absence of common annotation standards between different data sources. Results: In this article, we report a semi-automated methodology aimed at streamlining the process of metabolic network reconstruction by enabling the integration of different genome-wide databases of metabolic reactions. We present results obtained by applying this methodology to the metabolic network of the plant Arabidopsis thaliana. A systematic comparison of compounds and reactions between two genome-wide databases allowed us to obtain a high-quality core consensus reconstruction, which was validated for stoichiometric consistency. A lower level of consensus led to a larger reconstruction, which has a lower quality standard but provides a baseline for further manual curation. Conclusion: This semi-automated methodology may be applied to other organisms and help to streamline the process of genome-scale network reconstruction in order to accelerate the transfer of such models to applications.
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Publication type Article: Journal article
Document type Scientific Article
Keywords ESCHERICHIA-COLI; ARABIDOPSIS; MODEL; PLANT; ENVIRONMENT; PATHWAY; ONTOLOGY; WORLD
Language english
Publication Year 2010
HGF-reported in Year 2010
e-ISSN 1752-0509
Quellenangaben Volume: 4, Issue: , Pages: , Article Number: 114 Supplement: ,
Publisher Biomed Central Ltd.
Publishing Place London
Reviewing status Peer reviewed
POF-Topic(s) 30205 - Bioengineering and Digital Health
Research field(s) Enabling and Novel Technologies
PSP Element(s) G-505500-001
PubMed ID 20712863
Erfassungsdatum 2010-12-31