期刊
NATURE METHODS
卷 7, 期 3, 页码 S26-S41出版社
NATURE RESEARCH
DOI: 10.1038/NMETH.1431
关键词
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资金
- Mitocheck European Integrated Project [LSHG-CT-2004-503464]
- US National Institutes of Health (NIH) [P41 RR013642]
- Wellcome Trust
- ENFIN European Network of Excellence [LSHG-CT-2005-518254]
- British Heart Foundation [BS/06/001]
- BBSRC [E003443]
- NIH [R01 EB004155-03, P41 RR13218, 5 RL1 CA133834-03]
- NIH Roadmap for Medical Research [U54 RR021813, U54 EB005149]
- BBSRC [BB/G000883/1] Funding Source: UKRI
- MRC [MC_U127527203] Funding Source: UKRI
- Biotechnology and Biological Sciences Research Council [BB/G000883/1] Funding Source: researchfish
- Medical Research Council [G0700704B, MC_U127527203] Funding Source: researchfish
- NATIONAL CANCER INSTITUTE [RL1CA133834] Funding Source: NIH RePORTER
- NATIONAL CENTER FOR RESEARCH RESOURCES [P41RR013218, U54RR021813, P41RR013642] Funding Source: NIH RePORTER
- NATIONAL INSTITUTE OF BIOMEDICAL IMAGING AND BIOENGINEERING [U54EB005149, R01EB004155] Funding Source: NIH RePORTER
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.
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