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Tim Elston : Models and methods for studying cell movement

Most cells possess the ability to change morphology or migrate in response
to environmental cues. To understand the molecular mechanisms that drive
cell movement requires a systems-level approach that combines computational
approaches, including mathematical modeling and image analysis tools, with
high-resolution microscopy of living cells. Here we present several
examples for how such an integrated research strategy has been
successfully applied. First, we combine stochastic modeling with novel
biosensors for monitoring the spatiotemporal dynamics of Rho GTPase
activity to investigate the role of RhoG in cell polarization and
migration. Next, mathematical modeling and quantitative image analysis
methods are used to establish the role of cerebral cavernous malformation
(CCM) proteins in vascular tube formation. Finally, we present a novel
computational method for tracking and quantifying changes in cell shape.

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