Biological insights through omics data integration. Issue 15 (June 2019)

• Record Type: Journal Article
• Authors: Noor, Elad; Cherkaoui, Sarah; Sauer, Uwe
• Is Part Of: Current opinion in systems biology. Issue 15(2019)
• Page Start: 39
• Page End: 47
• Publication Date: 2019-06
• Subjects: Multiomics -- Data integration -- Machine learning -- Knowledge-based approaches -- Data-driven approaches; Systems biology -- Periodicals; 570
• DOI: 10.1016/j.coisb.2019.03.007
• Languages: English
• ISSNs: 2452-3100

Abstract

Abstract: The number of studies that collect and publish large-scale multiomics data is rapidly increasing. So far, we have not realized the full potential of the biological insights that can be drawn from integrating these data. In this review, we present the different existing approaches for such multiomics integration and highlight innovative articles that present new methods or biological insights. We claim that the difficulty in scaling remains one of the main reasons for the underuse of dynamic mechanistic models and discuss the potential of machine learning to disrupt this scientific field as it has done for many others.