Published in

Nature Research, Nature Methods, 3(9), p. 245-253, 2012

DOI: 10.1038/nmeth.1896

Links

Tools

Export citation

Search in Google Scholar

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

Journal article published in 2012 by Chris Allan, Jean-Marie Burel ORCID, Josh Moore ORCID, Colin Blackburn, Melissa Linkert, Scott Loynton, Donald MacDonald, William J. Moore, Carlos Neves, Andrew Patterson, Michael Porter, Aleksandra Tarkowska, Brian Loranger, Jerome Avondo, Ingvar Lagerstedt and other authors.
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

Full text: Download

Green circle
Preprint: archiving allowed
Upload
Orange circle
Postprint: archiving restricted
Upload
Red circle
Published version: archiving forbidden
Policy details
Data provided by SHERPA/RoMEO

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/. © 2012 Nature America, Inc. All rights reserved.