Find and compare the best bioinformatics tools for analyzing mitochondrial network morphology on conventional fluorescence microscopy images. Software tools are ranked by the biomedical research community.
Allows automatic reconstruction of entire tissue blocks. AnalyzeSkeleton calculates the optimum transformation at each pyramid level. It is able to store cellular-level phenotypic information. The tool (1) acquires images, (2) automatically and rigidly registers them, (3) segments the structures of interest, (4) groups their resulting contours, (5) locally or elastically refines registration, and (6) reconstructs structure in 3D based on the grouped contours.
Analyzes the extent of mitochondrial network fusion in cultured adherent mammalian cells. MiNA is able to identify and characterize morphological features of mitochondrial networks in multiple cell lines. It can detect differences in network fusion resulting from resveratrol treatment. The tool aims to estimate the mitochondrial network skeleton in representative images of a single cell and then compute values describing that skeleton.
Permits to measure mitochondrial interconnectivity and elongation from epifluorescence micrographs of cells immuno-stained. Mito-Morphology allows users to analyze mitochondria in the cell. It permits to specify if user want to measure mitochondria from another cell in the same field. The tool offers a polygon selection tool that allows to select the area of interest on a single cell to analyze.
Quantifies biological hallmarks and includes mitochondrial morphology and nuclear condensation. IDOTMETER allows to measure a variety of cellular changes, mainly involving autophagy and cell survival determinations, with high throughput in a simple and easy manner. The main advantage of this tool is to automatically extract and analyze all of the information from images of interest in a batch mode. Using software for high-throughput cell image analysis offers researchers the possibility of performing comprehensive and precise analysis of a high number of images in an automated manner, making this routine task easier.
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