title: Integration of metabolic databases for the reconstruction of genome-scale metabolic networks.
abstract: 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.
  
  
  CONCLUSIONS
  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.
authors: Faculty of Life Sciences, University of Manchester, Manchester M13 9PT, UK.
authors: Karin
authors: K
authors: Radrich
authors: Yoshimasa
authors: Y
authors: Tsuruoka
authors: Paul
authors: P
authors: Dobson
authors: Albert
authors: A
authors: Gevorgyan
authors: Neil
authors: N
authors: Swainston
authors: Gino
authors: G
authors: Baart
authors: Jean-Marc
authors: JM
authors: Schwartz
mesh_terms: D017360:Arabidopsis / Q000235:genetics / Q000378:metabolism; D016208:Databases, Factual; D016678:Genome; D023281:Genomics / Q000379:methods*; D053858:Metabolic Networks and Pathways; D015203:Reproducibility of Results