Rai Amit, Saito Kazuki
Graduate School of Pharmaceutical Sciences, Chiba University, 1-8-1 Inohana, Chuo-ku, Chiba 260-8675, Japan.
Graduate School of Pharmaceutical Sciences, Chiba University, 1-8-1 Inohana, Chuo-ku, Chiba 260-8675, Japan; RIKEN Center for Sustainable Resource Science, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan.
Curr Opin Biotechnol. 2016 Feb;37:127-134. doi: 10.1016/j.copbio.2015.10.010. Epub 2015 Dec 23.
Recent advancements in high-throughput large-scale analytical methods to sequence genomes of organisms, and to quantify gene expression, proteins, lipids and metabolites have changed the paradigm of metabolic modeling. The cost of data generation and analysis has decreased significantly, which has allowed exponential increase in the amount of omics data being generated for an organism in a very short time. Compared to progress made in microbial metabolic modeling, plant metabolic modeling still remains limited due to its complex genomes and compartmentalization of metabolic reactions. Herein, we review and discuss different omics-datasets with potential application in the functional genomics. In particular, this review focuses on the application of omics-datasets towards construction and reconstruction of plant metabolic models.
用于对生物体基因组进行测序以及对基因表达、蛋白质、脂质和代谢物进行定量分析的高通量大规模分析方法的最新进展，改变了代谢建模的模式。数据生成和分析的成本已大幅降低，这使得在极短时间内为一个生物体生成的组学数据量呈指数级增长。与微生物代谢建模取得的进展相比，植物代谢建模由于其复杂的基因组和代谢反应的区室化而仍然受到限制。在此，我们回顾并讨论了在功能基因组学中具有潜在应用价值的不同组学数据集。特别是，本综述重点关注组学数据集在植物代谢模型构建和重建中的应用。
