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Methods Mol Biol. 2018;1711:13-26. doi: 10.1007/978-1-4939-7493-1_2.

Discovering Altered Regulation and Signaling Through Network-based Integration of Transcriptomic, Epigenomic, and Proteomic Tumor Data.

Author information

1
Computational and Systems Biology, Massachusetts Institute of Technology, Cambridge, MA, USA.
2
Computational and Systems Biology, Massachusetts Institute of Technology, Cambridge, MA, USA. fraenkel-admin@mit.edu.
3
Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA. fraenkel-admin@mit.edu.

Abstract

With the extraordinary rise in available biological data, biologists and clinicians need unbiased tools for data integration in order to reach accurate, succinct conclusions. Network biology provides one such method for high-throughput data integration, but comes with its own set of algorithmic problems and needed expertise. We provide a step-by-step guide for using Omics Integrator, a software package designed for the integration of transcriptomic, epigenomic, and proteomic data. Omics Integrator can be found at http://fraenkel.mit.edu/omicsintegrator .

KEYWORDS:

Computational biology; Data integration; High-throughput data; Network biology

PMID:
29344883
PMCID:
PMC6309679
DOI:
10.1007/978-1-4939-7493-1_2
[Indexed for MEDLINE]
Free PMC Article

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