A Guide to Metabolic Network Modeling for Plant Biology

被引:1
作者
Rao, Xiaolan [1 ]
Liu, Wei [2 ]
机构
[1] Hubei Univ, Sch Life Sci, State Key Lab Biocatalysis & Enzyme Engn, Wuhan 430062, Peoples R China
[2] Tongji Univ, Shanghai East Hosp, Inst Regenerat Med, Sch Life Sci & Technol, Shanghai 200123, Peoples R China
来源
PLANTS-BASEL | 2025年 / 14卷 / 03期
关键词
plant metabolism; metabolic flux; metabolic modeling; machine learning; FLUX BALANCE ANALYSIS; LIGNIN BIOSYNTHESIS; C-4; PHOTOSYNTHESIS; MULTI-OMICS; GENOME; RECONSTRUCTION; ARABIDOPSIS; PREDICTION; RICE; COMPARTMENTALIZATION;
D O I
10.3390/plants14030484
中图分类号
Q94 [植物学];
学科分类号
071001 ;
摘要
Plants produce a diverse array of compounds that play crucial roles in growth, in development, and in responses to abiotic and biotic stresses. Understanding the fluxes within metabolic pathways is essential for guiding strategies aimed at directing metabolism for crop improvement and the plant natural product industry. Over the past decade, metabolic network modeling has emerged as a predominant tool for the integration, quantification, and prediction of the spatial and temporal distribution of metabolic flows. In this review, we present the primary methods for constructing mathematical models of metabolic systems and highlight recent achievements in plant metabolism using metabolic modeling. Furthermore, we discuss current challenges in applying network flux analysis in plants and explore the potential use of machine learning technologies in plant metabolic modeling. The practical application of mathematical modeling is expected to provide significant insights into the structure and regulation of plant metabolic networks.
引用
收藏
页数:18
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