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Moving the threshold slider selects which subregions are recognized as presenting the periodical structure.
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Our results match previous reports, this time with a quantitative unbiased approach. We validated its performance by an examination of the periodical structure in neurons at different developmental stages. It works by systematically interrogate the presence of the structure in images, by comparing subregions of the images to a reference pattern by means of their Pearson coefficient.
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Since its purpose is to find the spectrin rings, we named the software Gollum. With this in mind we developed a method and its implementation as an open-source image analysis tool for the automated quantification of the abundance and quality of protein periodic structures in images of biological samples. Since the function of the structure is not clear, a significant amount of work is still Quantitative studies call for automated image analysis tools that overcome these two major drawbacks. Plus, because such a task is time-consuming, only a small sample size can be analyzed, limiting the statistical relevance of results. So far, quantitative analysis of these structures has been done with correlation analysis with manual region selection, so there is a risk of introducing subjective bias. An example, first observed in 2013, is the alternating ring-like structure of actin and spectrin, wrapped around axons and repeated along them with a periodicity of around 190 nm. New microscopy techniques enabled the visualization of such protein periodic structures in their natural environment. Proteins frequently function in the form of regular or periodic, self-assembled structures, with typical sizes in the range of tens of nanometers. Automated quantification of periodical structures.
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