Note to users. If you're seeing this message, it means that your browser cannot find this page's style/presentation instructions -- or possibly that you are using a browser that does not support current Web standards. Find out more about why this message is appearing, and what you can do to make your experience of our site the best it can be.
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
The editors suggest the following Related Resources on Science sites:
In Science Magazine
REPORTS
Daniel Zicha, Ian M. Dobbie, Mark R. Holt, James Monypenny, Daniel Y. H. Soong, Colin Gray, and Graham A. Dunn (4 April 2003) Science300 (5616), 142.
[DOI: 10.1126/science.1082026] |Abstract »|Full Text »|PDF »|Supporting Online Material »
PERSPECTIVES
Paul Martin and Susan M. Parkhurst (4 April 2003) Science300 (5616), 63.
[DOI: 10.1126/science.1084148] |Summary »|Full Text »|PDF »
INTRODUCTION TO SPECIAL ISSUE
Stella M. Hurtley and Laura Helmuth (4 April 2003) Science300 (5616), 75.
[DOI: 10.1126/science.300.5616.75] |Summary »|PDF »
NEWS
Mary Beckman (4 April 2003) Science300 (5616), 76.
[DOI: 10.1126/science.300.5616.76] |Summary »|Full Text »|PDF »
NEWS
Greg Miller (4 April 2003) Science300 (5616), 78.
[DOI: 10.1126/science.300.5616.78] |Summary »|Full Text »|PDF »
NEWS
Caroline Seydel (4 April 2003) Science300 (5616), 80.
[DOI: 10.1126/science.300.5616.80] |Summary »|Full Text »|PDF »
DetecTiff(C): A Novel Image Analysis Routine for High-Content Screening Microscopy.
D. F. Gilbert, T. Meinhof, R. Pepperkok, and H. Runz (2009)
J Biomol Screen
14, 944-955
|Abstract »|PDF »
In Vivo Imaging of Mammalian Cells: Image Acquisition and Analysis.
J. R. Swedlow, P. D. Andrews, and M. Platani (2009)
CSH Protocols
2009, pdb.ip70
|Abstract »|Full Text »
Building a scientific data grid with DIGS.
M. G. Beckett, C. R. Allton, C. T.H. Davies, I. Davis, J. M. Flynn, E. J. Grant, R. S. Hamilton, A. C. Irving, R.D. Kenway, R. H. Ostrowski, et al. (2009)
Phil Trans R Soc A
367, 2471-2481
|Abstract »|Full Text »|PDF »
Announcing the JCB DataViewer, a browser-based application for viewing original image files.
Flexible informatics for linking experimental data to mathematical models via DataRail.
J. Saez-Rodriguez, A. Goldsipe, J. Muhlich, L. G. Alexopoulos, B. Millard, D. A. Lauffenburger, and P. K. Sorger (2008)
Bioinformatics
24, 840-847
|Abstract »|Full Text »|PDF »
Robust Hit Identification by Quality Assurance and Multivariate Data Analysis of a High-Content, Cell-Based Assay.
O. Durr, F. Duval, A. Nichols, P. Lang, A. Brodte, S. Heyse, and D. Besson (2007)
J Biomol Screen
12, 1042-1049
|Abstract »|PDF »
Loss of APC induces polyploidy as a result of a combination of defects in mitosis and apoptosis.
D. Dikovskaya, D. Schiffmann, I. P. Newton, A. Oakley, K. Kroboth, O. Sansom, T. J. Jamieson, V. Meniel, A. Clarke, and I. S. Nathke (2007)
J. Cell Biol.
176, 183-195
|Abstract »|Full Text »|PDF »
Automated tracking of gene expression in individual cells and cell compartments.
H. Shen, G. Nelson, D. E Nelson, S. Kennedy, D. G Spiller, T. Griffiths, N. Paton, S. G Oliver, M. R.H White, and D. B Kell (2006)
J R Soc Interface
3, 787-794
|Abstract »|Full Text »|PDF »
Automated local bright feature image analysis of nuclear protein distribution identifies changes in tissue phenotype.
D. W. Knowles, D. Sudar, C. Bator-Kelly, M. J. Bissell, and S. A. Lelievre (2006)
PNAS
103, 4445-4450
|Abstract »|Full Text »|PDF »
A Compendium of Signals and Responses Triggered by Prodeath and Prosurvival Cytokines.
S. Gaudet, K. A. Janes, J. G. Albeck, E. A. Pace, D. A. Lauffenburger, and P. K. Sorger (2005)
Mol. Cell. Proteomics
4, 1569-1590
|Abstract »|Full Text »|PDF »
Intravital multiphoton microscopy of dynamic renal processes.
B. A. Molitoris and R. M. Sandoval (2005)
Am J Physiol Renal Physiol
288, F1084-F1089
|Abstract »|Full Text »|PDF »
The Spatial Organization of Lipid Synthesis in the Yeast Saccharomyces cerevisiae Derived from Large Scale Green Fluorescent Protein Tagging and High Resolution Microscopy.
K. Natter, P. Leitner, A. Faschinger, H. Wolinski, S. McCraith, S. Fields, and S. D. Kohlwein (2005)
Mol. Cell. Proteomics
4, 662-672
|Abstract »|Full Text »|PDF »
Digital Microscopy Imaging and New Approaches in Toxicologic Pathology.
B. Mccullough, Xiaoyou Ying, T. Monticello, and M. Bonnefoi (2004)
Toxicol Pathol
32, 49-58
|Abstract »|PDF »
Light Microscopy Techniques for Live Cell Imaging.
