Automated dynamic cellular analysis in high throughput drug screens

To understand drug effects on cancer cells better, it is important to analyze cell nuclei dynamics from time-lapse fluorescence microscopy data. Existing methods, however, are rather limited in dealing with such time-lapse datasets while manual analysis is unreasonably time-consuming. We have therefore developed an automated system that can segment and track thousands of nuclei concurrently in time-lapse fluorescence microscopy data. Numerical nuclei features can be extracted based on our segmentation and tracking results. These features can be used for quantitative analysis of nuclei for high throughput drug screens.