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Data integration in the era of omics: current and future challenges

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Title: Data integration in the era of omics: current and future challenges
Authors: Gomez-Cabrero, D
Abugessaisa, I
Maier, D
Teschendorff, A
Merkenschlager, M
Gisel, A
Ballestar, E
Bongcam-Rudloff, E
Conesa, A
Tegner, J
Item Type: Journal Article
Abstract: To integrate heterogeneous and large omics data constitutes not only a conceptual challenge but a practical hurdle in the daily analysis of omics data. With the rise of novel omics technologies and through large-scale consortia projects, biological systems are being further investigated at an unprecedented scale generating heterogeneous and often large data sets. These data-sets encourage researchers to develop novel data integration methodologies. In this introduction we review the definition and characterize current efforts on data integration in the life sciences. We have used a web-survey to assess current research projects on data-integration to tap into the views, needs and challenges as currently perceived by parts of the research community.
Issue Date: 13-Mar-2014
Date of Acceptance: 1-Mar-2014
URI: http://hdl.handle.net/10044/1/71592
DOI: https://doi.org/10.1186/1752-0509-8-S2-I1
ISSN: 1752-0509
Publisher: BioMed Central
Journal / Book Title: BMC Systems Biology
Volume: 8
Issue: 2
Copyright Statement: © 2014 Gomez-Cabrero et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Sponsor/Funder: Commission of the European Communities
Funder's Grant Number: 306000
Keywords: Science & Technology
Life Sciences & Biomedicine
Mathematical & Computational Biology
WIDE ASSOCIATION
GENE-EXPRESSION
LIFE SCIENCES
HUMAN GENOME
DATA SETS
NETWORKS
METAANALYSIS
DISEASE
DIFFERENTIATION
BIOINFORMATICS
Animals
Biological Science Disciplines
Computational Biology
Data Collection
Humans
Research
Animals
Humans
Data Collection
Computational Biology
Research
Biological Science Disciplines
Science & Technology
Life Sciences & Biomedicine
Mathematical & Computational Biology
WIDE ASSOCIATION
GENE-EXPRESSION
LIFE SCIENCES
HUMAN GENOME
DATA SETS
NETWORKS
METAANALYSIS
DISEASE
DIFFERENTIATION
BIOINFORMATICS
Bioinformatics
1199 Other Medical and Health Sciences
Publication Status: Published
Article Number: I1
Online Publication Date: 2014-03-13
Appears in Collections:Institute of Clinical Sciences