School of Life Sciences, Oxford Brookes University, Headington, Oxford OX3 0BP, UK.
Biochem Soc Trans. 2010 Oct;38(5):1197-201. doi: 10.1042/BST0381197.
Reconstructing a model of the metabolic network of an organism from its annotated genome sequence would seem, at first sight, to be one of the most straightforward tasks in functional genomics, even if the various data sources required were never designed with this application in mind. The number of genome-scale metabolic models is, however, lagging far behind the number of sequenced genomes and is likely to continue to do so unless the model-building process can be accelerated. Two aspects that could usefully be improved are the ability to find the sources of error in a nascent model rapidly, and the generation of tenable hypotheses concerning solutions that would improve a model. We will illustrate these issues with approaches we have developed in the course of building metabolic models of Streptococcus agalactiae and Arabidopsis thaliana.
从注释基因组序列重建生物体的代谢网络模型，乍一看似乎是功能基因组学中最直接的任务之一，即使所需的各种数据源并非专为这种应用而设计。然而，与已测序的基因组相比，基因组规模的代谢模型数量却远远落后，除非模型构建过程能够得到加速，否则这种情况很可能会持续下去。有两个方面可以进行有益的改进，一是能够快速找到新生模型中的错误源，二是生成有关改进模型的可行假设。我们将通过构建酿脓链球菌和拟南芥代谢模型的过程中所开发的方法来说明这些问题。
