期刊
NATURE REVIEWS CARDIOLOGY
卷 18, 期 5, 页码 313-330出版社
NATURE PORTFOLIO
DOI: 10.1038/s41569-020-00477-1
关键词
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资金
- BHF [RG/16/14/32397]
- BIRAX Regenerative Medicine Initiative
- EU Horizon 2020 Research and Innovation Programme under Marie Skodowska-Curie grant [813716]
- Leducq Foundation [13CVD02, 18CVD02]
- Excellence Initiative VASCage (Centre for Promoting Vascular Health in the Ageing Community) of the Austrian Research Promotion Agency FFG (COMET program - Competence Centers for Excellent Technologies) - Austrian Ministry for Transport, Innovation and Tec [868624]
- Austrian Ministry for Digital and Economic Affairs
- federal state Tyrol (Standortagentur)
- federal state Salzburg (Vienna Business Agency)
- federal state Vienna (Vienna Business Agency)
- National Institute of Health Research (NIHR) Biomedical Research Centre based at Guy's and St Thomas' NHS (National Health Service) Foundation Trust
- King's College London
- King's College Hospital
- Marie Curie Actions (MSCA) [813716] Funding Source: Marie Curie Actions (MSCA)
Omics techniques generate large, multidimensional data that can be analyzed using informatics approaches and traditional statistical methods. Systems biology, utilizing network analysis and machine learning, addresses the complexity of biological processes. Novel approaches combining gene regulatory networks, proteomics, metabolomics, lipidomics, and phenomics with informatics techniques provide new insights into cardiovascular disease.
Omics techniques generate large, multidimensional data that are amenable to analysis by new informatics approaches alongside conventional statistical methods. Systems theories, including network analysis and machine learning, are well placed for analysing these data but must be applied with an understanding of the relevant biological and computational theories. Through applying these techniques to omics data, systems biology addresses the problems posed by the complex organization of biological processes. In this Review, we describe the techniques and sources of omics data, outline network theory, and highlight exemplars of novel approaches that combine gene regulatory and co-expression networks, proteomics, metabolomics, lipidomics and phenomics with informatics techniques to provide new insights into cardiovascular disease. The use of systems approaches will become necessary to integrate data from more than one omic technique. Although understanding the interactions between different omics data requires increasingly complex concepts and methods, we argue that hypothesis-driven investigations and independent validation must still accompany these novel systems biology approaches to realize their full potential. In this Review, Mayr and colleagues describe the growing number of omic techniques, discuss their strengths and weaknesses, outline network theory, and highlight exemplars of novel approaches that combine gene regulatory and co-expression networks, proteomics, metabolomics, lipidomics and phenomics with informatics techniques to provide new insights into cardiovascular disease.
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