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Visualization of Image Data from Cells to Organisms

1European Molecular Biology Laboratory, Heidelberg, Germany.
2Laboratory of Neuro Imaging, University of California, Los Angeles, Los Angeles, California, USA.
3Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, Edinburgh, UK.
4Medical and Radiological Sciences (Medical Physics), University of Edinburgh, Edinburgh, UK.
5Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA.
6Division of Biological Chemistry and Drug Discovery, College of Life Sciences, University of Dundee, Dundee, UK.
7The University of Queensland, Institute for Molecular Bioscience, Brisbane, Australia.
8Isomics, Inc., Cambridge, Massachusetts, USA.
9British Heart Foundation Experimental Magnetic Resonance Unit (BMRU), Department of Cardiovascular Medicine, University of Oxford, Oxford, UK.
10Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany.
Nature Publishing Group
Publication Date:
Volume Number:
Issue Number:
3 Suppl
Nat Methods. 2010 Mar;7(3 Suppl):S26-41.
PubMed ID:
Appears in Collections:
RL1 CA133834/CA/NCI NIH HHS/United States
U54 RR021813/RR/NCRR NIH HHS/United States
P41 RR013642/RR/NCRR NIH HHS/United States
R01 EB004155/EB/NIBIB NIH HHS/United States
P41 RR013218/RR/NCRR NIH HHS/United States
U54 EB005149/EB/NIBIB NIH HHS/United States
European Network of Excellence LSHG-CT-2005-518254
Mitocheck European Integrated Project LSHG-CT 2004-503464
Generated Citation:
Walter T., Shattuck D.W., Baldock R., Bastin M.E., Carpenter A.E., Duce S., Ellenberg J., Fraser A., Hamilton N., Pieper S., Ragan M.A., Schneider J.E., Tomancak P., Hériché J-K. Visualization of Image Data from Cells to Organisms. Nat Methods. 2010 Mar;7(3 Suppl):S26-41. PMID: 20195255. PMCID: PMC3650473.
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Advances in imaging techniques and high-throughput technologies are providing scientists with unprecedented possibilities to visualize internal structures of cells, organs and organisms and to collect systematic image data characterizing genes and proteins on a large scale. To make the best use of these increasingly complex and large image data resources, the scientific community must be provided with methods to query, analyze and crosslink these resources to give an intuitive visual representation of the data. This review gives an overview of existing methods and tools for this purpose and highlights some of their limitations and challenges.

Additional Material
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Walter-NMethS2010-fig1.jpg (155.259kB)