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

David Gomez-Cabrero, Imad Abugessaisa, Dieter Maier, Andrew Teschendorff, Matthias Merkenschlager, Andreas Gisel, Esteban Ballestar, Erik Bongcam-Rudloff, Ana Conesa, Jesper Tegnér

Research output: Contribution to journalReview articlepeer-review

277 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)I1
StatePublished - 2014
Externally publishedYes

Bibliographical note

Funding Information:
We would like to sincerely thank PhD Gordon Ball and PhD Ali Mortazavi for the constructive review of the manuscript. The supplement originated thanks to a Workshop co-organised by EU FP7 306000 STATegra and SeqAhead COST Action BM1006. The contribution of DGC, IA, DM, MM, EB, AC and JT was supported by EU FP7 306000 STATegra. The contribution of DGC was also supported by BILS ( The contribution of AG, EB and AC was supported by EU COST Action BM1006: SeqAhead. The contribution of AG and EB-R was supported by EU FP7 289452 ALLBIO. The contribution of JT was also supported by Stockholm County Council, and the Swedish Research Council. The contribution of IA was also supported by Åke Wibergs Stiftelsen medicine research Diarienr: 719593091 (

ASJC Scopus subject areas

  • Structural Biology
  • Modeling and Simulation
  • Molecular Biology
  • Computer Science Applications
  • Applied Mathematics


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