Understanding the heterogeneous dynamics of cellular processes requires not only tools to visualize molecular behavior but also versatile approaches to extract and analyze the information contained in live-cell movies of many cells. Automated identification and tracking of cellular features enable thorough and consistent comparative analyses in a high-throughput manner. Here, we present tools for two challenging problems in computational image analysis: (1) classification of motion for cells with complex shapes and dynamics and (2) segmentation of clustered cells and quantification of intracellular protein distributions based on a single fluorescence channel. We describe these methods and user-friendly software(1) (MATLAB applications with graphical user interfaces) so these tools can be readily applied without an extensive knowledge of computational techniques.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4504218 | PMC |
| http://dx.doi.org/10.1016/B978-0-12-420138-5.00022-7 | DOI Listing |
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