By applying convolutional neural network-based classifiers, we demonstrate that cell images can be robustly classified according to cell cycle phases. Combined with Grad-CAM analysis, our approach enables us to extract biological features underlying cellular phenomena of interest in an unbiased and data-driven manner.
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