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Open tools for storage and management of quantitative image data

Open tools for storage and management of quantitative image data

Research output: Chapter in Book/Report/Conference proceedingOther chapter contribution

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Authors

  • Joshua Moore
  • Chris Allan
  • Jean-Marie Burel
  • Brian Loranger
  • Donald MacDonald
  • Jonathan Monk
  • Jason R. Swedlow

Research units

Info

Original languageEnglish
Title of host publication Fluorescent Proteins
Place of publicationSan Diego
PublisherAcademic Press
Publication date2008
Pages555-+
Number of pages20
Volume85
Edition2nd
DOIs
StatePublished

Publication series

NameMethods in Cell Biology
PublisherElsevier
Volume85

Abstract

The explosion in quantitative imaging has driven the need to develop tools for storing, managing, analyzing, and viewing large sets of data. In this chapter, we discuss tools we have built for storing large data sets for the lifetime of a typical research project. As part of the Open Microscopy Environment (OME) Consortium, we have built a series of open-source tools that support the manipulation and visualization of large sets of complex image data. Images from a number of proprietary file formats can be imported and then accessed from a single server running in a laboratory or imaging facility. We discuss the capabilities of the OME Server, a Perl-based data management system that is designed for large-scale analysis of image data using a web browser-based user interface. In addition, we have recently released a lighter weight Java-based OME Remote Objects Server that supports remote applications for managing and viewing image data. Together these systems provide a suite of tools for large-scale quantitative imaging that is now commonly used throughout cell and developmental biology.

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