多组学研究综述及多组学数据分析、集成与应用

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引用次数: 0

摘要

多组学方法已经发展成为一种有益的植物系统技术,在医学和生物科学中流行的方法,强调了概述新的综合技术和功能以促进生物系统多尺度描述的必要性。通过不同的组学层来理解一个生物系统,揭示了可变性的补充来源,并可能推断出导致确定过程的病例序列。在PubMed检索论文及综述,检索关键词为:多组学、数据分析、组学、数据分析、数据集成、深度学习多组学、多组学集成。2010年以后发表的文章被优先考虑。作者主要关注开发新方法的流行出版物。组学揭示了在微生物群落中产生行为和相互作用数据的有趣工具,并且将组学细节整合到微生物风险评估中将对食品安全以及相关的腐败控制程序产生影响。组学数据集在分子水平上全面表征生物病例,在维度和复杂性上都在不断增加。多组学数据分析适用于治疗优化、分子检测和疾病预后,实现对疾病的机制认识。多组学数据分析的新有效解决方案以及精心设计的组件被推荐用于许多试验。这篇小型综述文章的目的是介绍多组学技术考虑不同的多组学分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Survey on Multi-omics, and Multi-omics Data Analysis, Integration and Application
Multi-omics approaches have developed as a profitable technique for plant systems, a popular method in medical and biological sciences underlining the necessity to outline new integrative technology and functions to facilitate the multi-scale depiction of biological systems. Understanding a biological system through various omics layers reveals supplementary sources of variability and probably inferring the sequence of cases leading to a definitive process. Manuscripts and reviews were searched on PubMed with the keywords of multi-omics, data analysis, omics, data analysis, data integration, deep learning multi-omics, and multi-omics integration. Articles that were published after 2010 were prioritized. The authors focused mainly on popular publications developing new approaches. Omics reveal interesting tools to produce behavioral and interactions data in microbial communities, and integrating omics details into microbial risk assessment will have an impact on food safety, and also on relevant spoilage control procedures. Omics datasets, comprehensively characterizing biological cases at a molecular level, are continually increasing in both dimensionality and complexity. Multi-omics data analysis is appropriate for treatment optimization, molecular testing and disease prognosis, and to achieve mechanistic understandings of diseases. New effective solutions for multi-omics data analysis together with well-designed components are recommended for many trials. The goal of this mini-review article is to introduce multi-omics technologies considering different multi-omics analyses.
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