Software platforms to facilitate reconstructing genome-scale metabolic networks

被引:50
作者
Hamilton, Joshua J. [1 ]
Reed, Jennifer L. [1 ]
机构
[1] Univ Wisconsin, Dept Chem & Biol Engn, Madison, WI 53706 USA
基金
美国国家科学基金会;
关键词
IN-SILICO; SYSTEMS-BIOLOGY; GLOBAL RECONSTRUCTION; MODELS; DATABASE; BALANCE; OPTIMIZATION; INTEGRATION; PREDICTION; TOOLS;
D O I
10.1111/1462-2920.12312
中图分类号
Q93 [微生物学];
学科分类号
071005 ; 100705 ;
摘要
System-level analyses of microbial metabolism are facilitated by genome-scale reconstructions of microbial biochemical networks. A reconstruction provides a structured representation of the biochemical transformations occurring within an organism, as well as the genes necessary to carry out these transformations, as determined by the annotated genome sequence and experimental data. Network reconstructions also serve as platforms for constraint-based computational techniques, which facilitate biological studies in a variety of applications, including evaluation of network properties, metabolic engineering and drug discovery. Bottom-up metabolic network reconstructions have been developed for dozens of organisms, but until recently, the pace of reconstruction has failed to keep up with advances in genome sequencing. To address this problem, a number of software platforms have been developed to automate parts of the reconstruction process, thereby alleviating much of the manual effort previously required. Here, we review four such platforms in the context of established guidelines for network reconstruction. While many steps of the reconstruction process have been successfully automated, some manual evaluation of the results is still required to ensure a high-quality reconstruction. Widespread adoption of these platforms by the scientific community is underway and will be further enabled by exchangeable formats across platforms.
引用
收藏
页码:49 / 59
页数:11
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