4.8 Review

Visualization of image data from cells to organisms

期刊

NATURE METHODS
卷 7, 期 3, 页码 S26-S41

出版社

NATURE RESEARCH
DOI: 10.1038/NMETH.1431

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资金

  1. Mitocheck European Integrated Project [LSHG-CT-2004-503464]
  2. US National Institutes of Health (NIH) [P41 RR013642]
  3. Wellcome Trust
  4. ENFIN European Network of Excellence [LSHG-CT-2005-518254]
  5. British Heart Foundation [BS/06/001]
  6. BBSRC [E003443]
  7. NIH [R01 EB004155-03, P41 RR13218, 5 RL1 CA133834-03]
  8. NIH Roadmap for Medical Research [U54 RR021813, U54 EB005149]
  9. BBSRC [BB/G000883/1] Funding Source: UKRI
  10. MRC [MC_U127527203] Funding Source: UKRI
  11. Biotechnology and Biological Sciences Research Council [BB/G000883/1] Funding Source: researchfish
  12. Medical Research Council [G0700704B, MC_U127527203] Funding Source: researchfish
  13. NATIONAL CANCER INSTITUTE [RL1CA133834] Funding Source: NIH RePORTER
  14. NATIONAL CENTER FOR RESEARCH RESOURCES [P41RR013218, U54RR021813, P41RR013642] Funding Source: NIH RePORTER
  15. NATIONAL INSTITUTE OF BIOMEDICAL IMAGING AND BIOENGINEERING [U54EB005149, R01EB004155] Funding Source: NIH RePORTER

向作者/读者索取更多资源

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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