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OMERO: flexible, model-driven data management for experimental biology

Nature Methods volume 9, pages 245–253 (2012)Cite this article

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Abstract

Data-intensive research depends on tools that manage multidimensional, heterogeneous datasets. We built OME Remote Objects (OMERO), a software platform that enables access to and use of a wide range of biological data. OMERO uses a server-based middleware application to provide a unified interface for images, matrices and tables. OMERO's design and flexibility have enabled its use for light-microscopy, high-content-screening, electron-microscopy and even non-image-genotype data. OMERO is open-source software, available at http://openmicroscopy.org/.

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Figure 1: Architecture and data modeling in OMERO.
Figure 2: OMERO clients.
Figure 3: External applications as OMERO clients.
Figure 4: Experimental, heterogeneous data stored and viewed in OMERO.
Figure 5: Non-image data and the use of metadata for large-scale computations.

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Acknowledgements

We thank E. Hill for helpful comments on the manuscript. Work on OME, Bio-Formats and OMERO in J.R.S.'s laboratory is supported by the Wellcome Trust (085982 and 095931) and the Biotechnology and Biological Sciences Research Council (BBSRC) (BB/G022585 and BB/I000755). Work on OMERO Electron Microscopy Data Bank at the European Bioinformatics Institute is supported by the BBSRC (BB/G022577). Work on OMERO at the John Innes Center, Norwich is supported by Joint Information Systems Committee (REXDAT03).

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  1. Christoph Best

    Present address: Present address: Google UK Ltd., London, UK.,

Authors and Affiliations

  1. Wellcome Trust Centre for Gene Regulation and Expression, College of Life Sciences, University of Dundee, Dundee, Scotland, UK

    Chris Allan, Jean-Marie Burel, Colin Blackburn, Scott Loynton, Donald MacDonald, William J Moore, Andrew Patterson, Michael Porter, Aleksandra Tarkowska, Brian Loranger, Katherine Hands, Ron T Hay & Jason R Swedlow

  2. Glencoe Software, Inc., Seattle, Washington, USA

    Chris Allan, Jean-Marie Burel, Josh Moore, Melissa Linkert, Carlos Neves & Jason R Swedlow

  3. John Innes Centre Norwich Research Park, Norwich, UK

    Jerome Avondo

  4. European Molecular B iology Laboratory– European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK

    Ingvar Lagerstedt, Ardan Patwardhan, Christoph Best & Gerard J Kleywegt

  5. CRS4, Pula, Italy

    Luca Lianas, Simone Leo & Gianluigi Zanetti

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Corresponding author

Correspondence to Jason R Swedlow.

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Competing interests

C.A., J.-M.B., J.M., C.N., M.L. and J.R.S. are affiliated with Glencoe Software, Inc., an open-source US-based commercial company that contributes to OMERO.

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Allan, C., Burel, JM., Moore, J. et al. OMERO: flexible, model-driven data management for experimental biology. Nat Methods 9, 245–253 (2012). https://doi.org/10.1038/nmeth.1896

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