The advent of super-resolution microscopy provided both a substantial improvement of the spatial resolution and the possibility to perform quantitative measurements at a nanometric level. In particular, single-molecule localization (SML) techniques provide a powerful tool to answer biological questions that require the observation of subcellular structures. Quantitative single-molecule analysis allows quantifying the number and observing the distribution of molecules in several biological systems beyond the diffraction limit [1]. In the last few years, many computational methods employing clustering analysis algorithms [2] have been developed to extract quantitative information from SML data sets.
Unveiling the Inhibitory Synapse Organization Using Superresolution Microscopy
Scalisi, Silvia;Diaspro, Alberto
2019-01-01
Abstract
The advent of super-resolution microscopy provided both a substantial improvement of the spatial resolution and the possibility to perform quantitative measurements at a nanometric level. In particular, single-molecule localization (SML) techniques provide a powerful tool to answer biological questions that require the observation of subcellular structures. Quantitative single-molecule analysis allows quantifying the number and observing the distribution of molecules in several biological systems beyond the diffraction limit [1]. In the last few years, many computational methods employing clustering analysis algorithms [2] have been developed to extract quantitative information from SML data sets.
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