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整合代谢数据库以重建基因组规模的代谢网络。

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

作者信息

Radrich Karin, Tsuruoka Yoshimasa, Dobson Paul, Gevorgyan Albert, Swainston Neil, Baart Gino, Schwartz Jean-Marc

机构信息

Faculty of Life Sciences, University of Manchester, Manchester M13 9PT, UK.

出版信息

BMC Syst Biol. 2010 Aug 16;4:114. doi: 10.1186/1752-0509-4-114.

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.

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.

摘要

背景

基因组规模的代谢重建已被公认为是一种有价值的工具,可用于从代谢工程到进化研究等各种应用。然而,此类网络的重建仍然是一个艰巨的过程,需要高水平的人工干预。由于存在缺失或冲突信息,以及不同数据源之间缺乏通用注释标准,这一过程变得更加复杂。

结果

在本文中,我们报告了一种半自动方法,旨在通过整合不同的全基因组代谢反应数据库来简化代谢网络重建过程。我们展示了将该方法应用于植物拟南芥代谢网络所获得的结果。对两个全基因组数据库之间的化合物和反应进行系统比较,使我们能够获得高质量的核心共识重建,并对其化学计量一致性进行了验证。较低水平的共识导致了更大规模的重建,其质量标准较低,但为进一步的人工编目提供了基线。

结论

这种半自动方法可应用于其他生物体,并有助于简化基因组规模网络重建过程,以加速此类模型向应用的转化。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e840/2930596/66a3782f0220/1752-0509-4-114-1.jpg

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