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Informatics and Quantitative Analysis in Biological Imaging
Jason R. Swedlow,1*Ilya Goldberg,2Erik Brauner,3Peter K. Sorger34
Biological imaging is now a quantitative technique
for probing cellular structure and dynamics and is increasingly used
forcell-based screens. However, the bioinformatics tools requiredfor
hypothesis-driven analysis of digital images are still immature.We are
developing the Open Microscopy Environment (OME) as aninformatics
solution for the storage and analysis of optical microscopeimage data.
OME aims to automate image analysis, modeling, andmining of large sets
of images and specifies a flexible data model,a relational database,
and an XML-encoded file standard that isusable by potentially any
software tool. With this design, OMEprovides a first step toward
biological image informatics.
1 Division of Gene Regulation and Expression,
Wellcome Trust Biocentre, University of Dundee, Dow Street, Dundee DD1
5EH, Scotland.
2 Laboratory of Genetics, National
Institute on Aging, National Institutes of Health, 333 Cassell Drive,
Suite 4000, Baltimore, MD 21224, USA.
3 Institute of
Chemistry and Cell Biology, Harvard Medical School, 250 Longwood
Avenue, Boston, MA 02115, USA.
4 Department of
Biology, Massachusetts Institute of Technology, 77 Massachusetts
Avenue, Cambridge, MA 02139, USA.
*
To whom correspondence should be addressed. E-mail:
j.swedlow{at}dundee.ac.uk
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