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Raw Data to Results: A Hands-On Introduction and Overview of Computational Analysis for Single-Molecule Localization Microscopy

Koen J.A. Martens, Bartosz Turkowyd, Ulrike Endesfelder

2022Frontiers in Bioinformatics20 citationsDOIOpen Access PDF

Abstract

Single-molecule localization microscopy (SMLM) is an advanced microscopy method that uses the blinking of fluorescent molecules to determine the position of these molecules with a resolution below the diffraction limit (∼5-40 nm). While SMLM imaging itself is becoming more popular, the computational analysis surrounding the technique is still a specialized area and often remains a "black box" for experimental researchers. Here, we provide an introduction to the required computational analysis of SMLM imaging, post-processing and typical data analysis. Importantly, user-friendly, ready-to-use and well-documented code in Python and MATLAB with exemplary data is provided as an interactive experience for the reader, as well as a starting point for further analysis. Our code is supplemented by descriptions of the computational problems and their implementation. We discuss the state of the art in computational methods and software suites used in SMLM imaging and data analysis. Finally, we give an outlook into further computational challenges in the field.

Topics & Concepts

Python (programming language)Computer scienceMATLABComputational scienceComputer graphics (images)SoftwareMicroscopyComputational modelArtificial intelligenceProgramming languageOpticsPhysicsAdvanced Fluorescence Microscopy TechniquesAdvanced Electron Microscopy Techniques and ApplicationsAdvanced Biosensing Techniques and Applications
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