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BioImageXD
Analyzes, processes and visualizes multi-dimensional microscopy images. BioImageXD puts open-source computer science tools for three-dimensional visualization and analysis into the hands of all researchers, through a user-friendly graphical interface tuned to the needs of biologists. BioImageXD has no restrictive licenses or undisclosed algorithms and enables publication of precise, reproducible and modifiable workflows. It allows simple construction of processing pipelines and should enable biologists to perform challenging analyses of complex processes.
MosaicIA / Mosaic Interaction Analysis
Allows spatial point pattern and interaction analysis. MosaicIA provides standardized ways to (1) correct for the influence of the distribution of points within one set onto the distance distribution to another set; (2) infer parameters of the interaction potential, such as the strength and length scale of the interaction; (3) perform statistical hypothesis tests for the presence of an interaction. It has been tested on both synthetic and real-world data.
CDA / Confined Displacement Algorithm Determines True and Random Colocalization
Provides a method for determining true and random colocalization for experimental scenarios. CDA calculates modified Manders coefficients, M1ROI and M2ROI and detects colocalization in cellular and subcellular compartments thanks to standard confocal microscopy and computational image correlation techniques. The module can be used through the ImageJ software and can be applied to various fields including fluorescent wide field or confocal microscopy.
Colocalization Threshold
Allows users to set the thresholds for colocalization analysis. Colocalization can generate a 2D Histogram/Scatterplot/Fluorogram useful for visualizing the correlation of the pixel intensities, over all pixels/voxels in the image. It also makes a linear regression fit of the data in the scatter plot. It does auto threshold determination, and uses an iterative procedure to determine what pair of thresholds for the 2 channels of the scatterplot give a Pearson's correlation coefficient (r) of zero for the pixels below the thresholds.
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