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Spatial Temporal Stochastic Models in Fluorescence Microscopy with applications to Cell Biology

Our major goal is to model and analyze dynamic procesess from image sequences using spatial temporal stochastic processes: spatial temporal point processes and temporal random sets. We apply them to study the basic mechanisms of membrane traffic: exocytosis and endocytosis.

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• Analysis of protein-protein spatial-temporal dependencies from TIRFM image sequences using temporal random sets

• Detection of dense-core vesicles from electron microscopy images and analysis of their intracellular distribution

• Counting endocytic events and estimation of their durations from TIRFM image sequences using temporal Boolean models

• Detection of exocytosis from TIRFM image sequences. Spatial-temporal analysis of fusions maps

^{Acknowledgement}

^{We thank the Human Frontier Science Organization Program, RGY-40/2003 app.dimensions.ai , and the Spanish Ministry of Science and Education for their financial support, TIN2007-67587 (FEDER FUNDS).}

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