Omics data input for metabolic modeling

被引：37
作者：
Rai, Amit [1 ]
Saito, Kazuki [1 ,2 ]
机构：
[1] Chiba Univ, Grad Sch Pharmaceut Sci, Chuo Ku, 1-8-1 Inohana, Chiba 2608675, Japan
[2] RIKEN Ctr Sustainable Resource Sci, Tsurumi Ku, 1-7-22 Suehiro Cho, Yokohama, Kanagawa 2300045, Japan
来源：
CURRENT OPINION IN BIOTECHNOLOGY | 2016年 / 37卷
关键词：
C-13 FLUX ANALYSIS; NETWORK RECONSTRUCTION; FUNCTIONAL ANNOTATION; RNA-SEQ; ARABIDOPSIS; GENOMICS; INTEGRATION; EXPRESSION; PROTEOMICS; PATHWAYS;
D O I：
10.1016/j.copbio.2015.10.010
中图分类号：
Q5 [生物化学];
学科分类号：
071010 ; 081704 ;
摘要：
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.
引用
收藏
页码：127 / 134
页数：8
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