物候学
表观遗传学
代谢组学
数据科学
基因组学
农业
蛋白质组学
计算生物学
生物
生物技术
生物信息学
计算机科学
生态学
基因组
遗传学
基因
基因表达
DNA甲基化
作者
Juexin Wang,Sidharth Sen,Shuai Zeng,Yuexu Jiang,Yen On Chan,Zhen Lyu,Tyler McCubbin,Rachel A. Mertz,Robert E. Sharp,Trupti Joshi
摘要
Abstract Advances in next‐generation sequencing and other high‐throughput technologies have facilitated multiomics research, such as genomics, epigenomics, transcriptomics, proteomics, metabolomics, and phenomics. The resultant emerging multiomics data have brought new challenges as well as opportunities, as seen in the plant and agriculture science domains. We reviewed several bioinformatic and computational methods, models, and platforms, and we have highlighted some of our in‐house developed efforts aimed at multiomics data analysis, integration, and management issues faced by the research community. A case study using multiomics datasets generated from our studies of maize nodal root growth under water deficit stress demonstrates the power of these datasets and some other publicly available tools. This analysis also sheds light on the landscape of such applied bioinformatic tools currently available for plant and crop science studies and introduces emerging trends and how they may affect the future.
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