VISION — an open-source software for automated multi-dimensional image analysis of cellular biophysics
It contains data sets from Weber et al, Journal of Cell Science, 2024 (https://doi.org/10.1242/jcs.262166) The details for citation provided in the README file. Please cite this item as: Florian Weber, Sofiia Iskrak, Franziska Ragaller, Jan Schlegel, Birgit Plochberger, Erdinc Sezgin, Luca A. Andronico DOI: 10.17044/scilifelab.26233184 It contains microscopy images and excel sheets of the data. Abstract: Environment-sensitive probes are frequently used in spectral/multi-channel microscopy to study alterations in cell homeostasis. However, the few open-source packages available for processing of spectral images are limited in scope. Here, we present VISION, a stand-alone software based on Python for spectral analysis with improved applicability. In addition to classical intensity-based analysis, our software can batch-process multidimensional images with an advanced single-cell segmentation capability and apply user-defined mathematical operations on spectra to calculate biophysical and metabolic parameters of single cells. VISION allows for 3D and temporal mapping of properties such as membrane fluidity and mitochondrial potential. We demonstrate the broad applicability of VISION by applying it to study the effect of various drugs on cellular biophysical properties; the correlation between membrane fluidity and mitochondrial potential; protein distribution in cell-cell contacts; and properties of nanodomains in cell-derived vesicles. Together with the code, we provide a graphical user interface for facile adoption. Data usage Researchers are welcome to use the data contained in the dataset for any projects. Please cite this item upon use or when published. We encourage reuse using the same CC BY 4.0 License. Data Content lsm or czi files for confocal and spectral images tif files for super-resolution images Excel files for graphs Software to open files .xlsx - Microsoft Excel .tif, .lsm, .czi - Fiji (https://imagej.net/software/fiji/)
Human biophysics
Computational imaging
Landing page for the dataset
Landningssida för datasetet
Karolinska Institutet