Fig. 1 | Scientific Reports

Fig. 1

From: A computational pipeline for image-based statistical analysis of biomolecular condensates dynamics using morphological descriptors

Fig. 1

Biomolecular condensation analysis pipeline. Fluorescently labeled biological macromolecule(s) is(are) pipetted together with modulatory factor(s) stock solution in a 96 or 384-well plate. The plate is then positioned in the Operetta HCT (PerkinElmer) imaging platform. Fluorescence images are collected at 40X WD objective following a z-scan. Stored images are assembled with experimental metadata and processed in an HPC container-based parallelized image analysis pipeline using Python scripts. Raw images are segmented following normalization, denoising and enhancement of the raw images. Cropped objects are removed from the borders of the image. Fluorescence intensity of droplets is quantified by applying the cleaned binary masks to the raw images. Background is identified as the inverse of binary and eroded to avoid light scattering from the droplets. Morphology descriptors are then extracted and resulting dataframe are assembled for further statistical analysis.

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