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Front Genet. 2017 Jun 16;8:84. doi: 10.3389/fgene.2017.00084. eCollection 2017.

More Is Better: Recent Progress in Multi-Omics Data Integration Methods.

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Epidemiology Program, University of Hawaii Cancer CenterHonolulu, HI, United States.
Molecular Biosciences and Bioengineering Graduate Program, University of Hawaii at ManoaHonolulu, HI, United States.
Department of Obstetrics, Gynecology, and Women's Health, John A. Burns School of Medicine, University of Hawaii at ManoaHonolulu, HI, United States.


Multi-omics data integration is one of the major challenges in the era of precision medicine. Considerable work has been done with the advent of high-throughput studies, which have enabled the data access for downstream analyses. To improve the clinical outcome prediction, a gamut of software tools has been developed. This review outlines the progress done in the field of multi-omics integration and comprehensive tools developed so far in this field. Further, we discuss the integration methods to predict patient survival at the end of the review.


integration; multi-omics; precision medicine; prediction; prognosis; supervised learning; unsupervised learning

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