title: Data integration in the era of omics: current and future challenges.
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.
authors.forename: David
authors.initials: D
authors.lastname: Gomez-Cabrero
authors.forename: Imad
authors.initials: I
authors.lastname: Abugessaisa
authors.forename: Dieter
authors.initials: D
authors.lastname: Maier
authors.forename: Andrew
authors.initials: A
authors.lastname: Teschendorff
authors.forename: Matthias
authors.initials: M
authors.lastname: Merkenschlager
authors.forename: Andreas
authors.initials: A
authors.lastname: Gisel
authors.forename: Esteban
authors.initials: E
authors.lastname: Ballestar
authors.forename: Erik
authors.initials: E
authors.lastname: Bongcam-Rudloff
authors.forename: Ana
authors.initials: A
authors.lastname: Conesa
authors.forename: Jesper
authors.initials: J
authors.lastname: Tegnér
mesh_terms: D000818:Animals; D001690:Biological Science Disciplines; D019295:Computational Biology / Q000379:methods* / Q000592:standards; D003625:Data Collection; D006801:Humans; D012106:Research