Spatiotemporal image analysis of cytoskeletal dynamics

Imaging of recombinant fluorescent proteins in living cells has become a very useful and widely applied tool in cell biology and has been awarded with the 2008 Nobel prize in chemistry. Our project focuses on the intermediate filament cytoskeleton that forms a complex 3D-scaffolding which is subject to continuous turnover and adjusts rapidly to altering conditions. This complex scaffold is needed for many basic cell functions. It generates cell shape, produces locomotion, provides mechanical strength and facilitates intracellular transport. Consequently, nearly all cell functions including signaling pathways are connected to and interact with this framework. Therefore, understanding cytoskeletal functions is a prerequisite to understand diseases like cancer or the action of drugs. A major challenge is to design algorithms for the quantitative evaluation of the vast amount of image data generated by recent confocal microscopes. Our goal is therefore to develop image processing algorithms that are capable of analyzing and quantifying such data with particular emphasis on the movement determination of shape-changing fluorescent protein-labeled structures. The novel algorithms are expected to provide answers to a number of pertinent and still unresolved questions concerning this abundant filament system.



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