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Issue 1, 2018
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Data integration and predictive modeling methods for multi-omics datasets

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Abstract

Translating data to knowledge and actionable insights is the Holy Grail for many scientific fields, including biology. The unprecedented massive and heterogeneous data have created as many challenges to store, process and analyze as the opportunities and promises they hold. Here, we provide an overview of these opportunities and challenges in multi-omics predictive analytics.

Graphical abstract: Data integration and predictive modeling methods for multi-omics datasets

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Publication details

The article was received on 04 Oct 2017, accepted on 30 Oct 2017 and first published on 20 Dec 2017


Article type: Review Article
DOI: 10.1039/C7MO00051K
Citation: Mol. Omics, 2018,14, 8-25
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    Data integration and predictive modeling methods for multi-omics datasets

    M. Kim and I. Tagkopoulos, Mol. Omics, 2018, 14, 8
    DOI: 10.1039/C7MO00051K

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