背景(考古学)
植物代谢
数据科学
代谢网络
计算机科学
大数据
可视化
光学(聚焦)
数据集成
基因组
计算生物学
生物
人工智能
数据挖掘
基因
光学
物理
古生物学
核糖核酸
生物化学
作者
Léo Gerlin,Clément Frainay,Fabien Jourdan,Caroline Baroukh,Sylvain Prigent
出处
期刊:Elsevier eBooks
[Elsevier]
日期:2021-01-01
卷期号:: 237-270
标识
DOI:10.1016/bs.abr.2020.09.021
摘要
With the development of plant metabolomics, projects like the 10,000 plants genome sequencing project and the growth of other omics, the amount of data describing plant metabolism has never been so big. Genome-scale metabolic models (GEMs) are widely used to integrate and study the available information, and to better understand global responses to metabolic changes. In the first part of this chapter, we will focus on the existing plant GEMs, their history, and the biological questions associated with their reconstruction. Those GEMs were initially reconstructed based on cell suspension systems, but current reconstructions are widely focused on multiorgans and multitissues models, requiring some model integration. Model integration is the focus of the second part of this chapter, with the study of biotic interactions with the integration of GEMs coming from plant-interacting microorganisms and their host plants, modeling either pathogenic and symbiotic interactions. Emphasis will be placed on modeling quantitative interaction between plants and microorganisms. Finally, the third part of this chapter describes how the visualization of networks could be used to improve the understanding of the models and the integration of different omics data, and how good representation of metabolic networks can help the user to perform diverse tasks and put knowledge in context.
科研通智能强力驱动
Strongly Powered by AbleSci AI