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Get Free AccessIntroduction: Among super-resolved microscopy (SRM) methods, single molecule localisation microscopy techniques, such as photo-activated localisation microscopy (PALM) [l] and stochastic optical reconstruction microscopy (STORM) [2], enable imaging beyond the classical diffraction limit to gain new insights in subcellular biological processes with relatively simple instrumentation. This has led to a number of low-cost instruments, e.g. for STORM microscopy [3-6], which can benefit from an array of software tools for the single molecule localisation microscopy (SMLM) data analysis [7]. Our low-cost “easySTORM approach [4] implements dSTORM [8] with multimode diode lasers and optical fibres to provide STORM images with fields of view up to ~125 μm diameter using μManager [9] to control the image data acquisition and ThunderSTORM [10] to analyse the SMLM data. We and others [11,12] are motivated to develop automated SMLM for high content analysis (HCA) that enable rapid imaging of sample arrays, allows statistical analysis of samples that may vary in terms of labelling and biological heterogeneity and enable moderate throughput screening applications.
Frederik Görlitz, Jonathan Lightley, Sunil Kumar, Edwin García, Ming Yan, Riccardo Wysoczanski, Yuriy Alexandrov, Jonathan Baker, Peter J Barnes, Ian Munro, Louise Donnelly, Christopher Dunsby, Mark A. A. Neil, Paul M. W. French (2019). Automated multiwell plate STORM: towards open source super-resolved high content analysis. , DOI: https://doi.org/10.1117/12.2526940.
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Type
Article
Year
2019
Authors
14
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.1117/12.2526940
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