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Shaul Yogev

Publications and source records attributed to Shaul Yogev.

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MTQuant: "Seeing" Beyond the Diffraction Limit in Fluorescence Images to Quantify Neuronal Microtubule Organization

MotivationMicrotubules (MTs) are polarized polymers that are critical for cell structure and axonal transport. They form a bundle in neurons, but beyond that, their organization is relatively unstudied.\n\nResultsWe present MTQuant, a method for quantifying MT organization using light microscopy, which distills three parameters from MT images: the spacing of MT minus-ends, their average length, and the average number of MTs in a cross-section of the bundle. This method allows for robust and rapid in vivo analysis of MTs, rendering it more practical and more widely applicable than commonly-used electron microscopy reconstructions. MTQuant was successfully validated with three ground truth data sets and applied to over 3000 images of MTs in a C. elegans motor neuron.\n\nAvailabilityMATLAB code is available at http://roscoope.github.io/MTQuant\n\nContacthorowitz@stanford.edu\n\nSupplementary informationSupplementary data are available at Bioinformatics online.

Bioinformatics