Single-molecule localization (SML) techniques provide a powerful tool to answer biological questions requiring the observation of subcellular structures at the nanoscale. Quantitative single-molecule analysis allows quantifying the number and distribution of molecules in several biological systems beyond the diffraction limit [1]. In the last few years, many computational methods employing clustering analysis algorithms have been developed to extract quantitative information from SML data sets. In neuroscience, quantitative SML has been applied to reveal density and spatial organization of synaptic proteins

Quantitative Super-Resolution Microscopy of Proteins at the Synaptic Level

Scalisi, Silvia;Diaspro, Alberto;Cella Zanacchi, Francesca
2018

Abstract

Single-molecule localization (SML) techniques provide a powerful tool to answer biological questions requiring the observation of subcellular structures at the nanoscale. Quantitative single-molecule analysis allows quantifying the number and distribution of molecules in several biological systems beyond the diffraction limit [1]. In the last few years, many computational methods employing clustering analysis algorithms have been developed to extract quantitative information from SML data sets. In neuroscience, quantitative SML has been applied to reveal density and spatial organization of synaptic proteins
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/892236
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