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How to interpret and integrate multi-omics data at systems level

Animal Cells and Systems 2020년 24권 1호 p.1 ~ 7
정건태, 김광표, 김권일,
소속 상세정보
정건태 ( Jung Gun-Tae ) - Kyung Hee University Department of Biomedical Science and Technology
김광표 ( Kim Kwang-Pyo ) - Kyung Hee University Department of Biomedical Science and Technology
김권일 ( Kim Kwon-Eel ) - Kyung Hee University Department of Biology

Abstract


Current parallel sequencing technologies generate biological sequence data explosively and enable omics studies that analyze collective biological features. The more omics data that is accumulated, the more they show the regulatory complexity of biological phenotypes. This high order regulatory complexity needs systems-level approaches, including network analysis, to understand it. There are a series of layers in the omics field that are closely connected to each other as described in ‘central dogma.’ We, therefore, have to not only interpret each single omics layer but also to integrate multi-omics layers systematically to get a full picture of the regulatory landscape of the biological phenotype. Especially, individual omics data has their own adequate biological network to apply systematic analysis appropriately. A full regulatory landscape can only be obtained when multi-omics data are incorporated within adequate networks. In this review, we discuss how to interpret and integrate multi-omics data systematically using recent studies. We also propose an analysis framework for systematic multi-omics interpretation by centering on the transcriptional core regulator, which can be incorporated in all omics networks.

키워드

Multi-omics; co-expression network; transcriptional regulatory network; protein interactome network; transcriptional core regulator

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