Survey on Multi-omics, and Multi-omics Data Analysis, Integration and Application

Abstract

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.