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Code and data belonging to "Raw data to results: a hands-on introduction and overview of computational analysis for single-molecule localization microscopy", Martens et al., (2022), Frontiers in Bioinformatics (https://www.frontiersin.org/articles/10.3389/fbinf.2021.817254).

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Computational introduction to SMLM data analysis

Code and data belonging to "Raw data to results: a hands-on introduction and overview of computational analysis for single-molecule localization microscopy", Martens et al., (2022), Frontiers in Bioinformatics (https://www.frontiersin.org/articles/10.3389/fbinf.2021.817254).

In this github repository, the MATLAB scripts are located. The Python colab workbooks can be accessed at https://colab.research.google.com/drive/1fn837sOJSaq2xWdgcmgR4bkGv8ePW2yj . Additionally, the data is stored in the /Data folder.

MATLAB instructions

To use the MATLAB modules, download/clone this entire repository, make it the main folder within MATLAB, and include all sub-folders. Then the individual modules can be opened within MATLAB and run.

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Code and data belonging to "Raw data to results: a hands-on introduction and overview of computational analysis for single-molecule localization microscopy", Martens et al., (2022), Frontiers in Bioinformatics (https://www.frontiersin.org/articles/10.3389/fbinf.2021.817254).

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