4.6 Review

NanoJ: a high-performance open-source super-resolution microscopy toolbox

期刊

出版社

IOP Publishing Ltd
DOI: 10.1088/1361-6463/ab0261

关键词

super-resolution microscopy; ImageJ; Fiji; image analysis; image quality assessment; fluidics; single-particle analysis

资金

  1. UK Biotechnology and Biological Sciences Research Council [BB/M022374/1, BB/P027431/1, BB/R000697/1, BB/S507532/1]
  2. UK Medical Research Council [MR/K015826/1]
  3. Wellcome Trust [203276/Z/16/Z]
  4. European Research Council [649101-UbiProPox]
  5. Centre National de la Recherche Scientifique (CNRS ATIP-AVENIR program AO2016)
  6. Engineering and Physical Sciences Research Council [EP/L504889/1]
  7. UK's Biotechnology and Biological Sciences Research Council
  8. Cancer Research UK [C1529/A17343]
  9. BBSRC [BB/P001440/1]
  10. MRC [MC_CF12266]
  11. 4 year MRC Research Studentship
  12. Swedish Research Council [621-20134685]
  13. UCL
  14. [MC_UU12018/7]
  15. BBSRC [BB/P001440/1, BB/R021805/1, BB/P027431/1, BB/M022374/1, BB/R000697/1] Funding Source: UKRI
  16. MRC [MR/K015826/1] Funding Source: UKRI

向作者/读者索取更多资源

Super-resolution microscopy (SRM) has become essential for the study of nanoscale biological processes. This type of imaging often requires the use of specialised image analysis tools to process a large volume of recorded data and extract quantitative information. In recent years, our team has built an open-source image analysis framework for SRM designed to combine high performance and ease of use. We named it NanoJ-a reference to the popular ImageJ software it was developed for. In this paper, we highlight the current capabilities of NanoJ for several essential processing steps: spatio-temporal alignment of raw data (NanoJ-Core), super-resolution image reconstruction (NanoJ-SRRF), image quality assessment (NanoJ-SQUIRREL), structural modelling (NanoJ-VirusMapper) and control of the sample environment (NanoJ-Fluidics). We expect to expand NanoJ in the future through the development of new tools designed to improve quantitative data analysis and measure the reliability of fluorescent microscopy studies.

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