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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.

Author information

1
Epidemiology Program, University of Hawaii Cancer CenterHonolulu, HI, United States.
2
Molecular Biosciences and Bioengineering Graduate Program, University of Hawaii at ManoaHonolulu, HI, United States.
3
Department of Obstetrics, Gynecology, and Women's Health, John A. Burns School of Medicine, University of Hawaii at ManoaHonolulu, HI, United States.

Abstract

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.

KEYWORDS:

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

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