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• W1941998953 abstract "Summary Robotic, high‐throughput microscopy is a powerful tool for small molecule screening and classifying cell phenotype, proteomic and genomic data. An important hurdle in the field is the automated classification and visualization of results collected from a data set of tens of thousands of images. We present a method that approaches these problems from the perspective of flow cytometry with supporting open‐source code. Image analysis software was created that allowed high‐throughput microscopy data to be analysed in a similar manner as flow cytometry. Each cell on an image is considered an object and a series of gates similar to flow cytometry is used to classify and quantify the properties of cells including size and level of fluorescent intensity. This method is released with open‐source software and code that demonstrates the method's implementation. Accuracy of the software was determined by measuring the levels of apoptosis in a primary murine myoblast cell line after exposure to staurosporine and comparing these results to flow cytometry." @default.
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• W1941998953 date "2013-01-16" @default.
• W1941998953 modified "2023-10-17" @default.
• W1941998953 title "Automated classification and visualization of fluorescent live cell microscopy images" @default.
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• W1941998953 doi "https://doi.org/10.1111/jmi.12010" @default.
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