Automatic detection of dense-core vesicles in secretory cells and statistical analysis of their intracellular
We model the locations of large dense-core vesicles (granules) within the cytoplasm
as a realization of a finite spatial point process. We have developped an image processing method to segment the
granules from electron microscopy images. The relative locations of the
granules with respect to the plasma membrane are characterized by the empirical cumulative distribution function of the
distances from the granules to the plasma membrane and the density
of granules within a given distance to the plasma membrane. The
descriptors of the different cells for each group are compared using
bootstrap procedures. Our results show these functional descriptors and the
testing procedure allow to discriminate between control and mutant
cells. The application of these novel tools to studies of secretion
should help in the analysis of diseases associated with dysfunctional secretion.
Software
Publications
- Díaz E, Ayala G, Díaz ME, Gong LW, Toomre D. Automatic detection of dense core vesicles in secretory cells and statistical analysis of their intracellular distribution. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 7(1):2-11, 2010
- Gong L, Di Paolo G, Diaz E, Cestra G, Díaz ME, Lindau M, De Camilli P, Toomre D. PIP Kinase Type Ig Regulates Dynamics of Large Dense-Core Vesicle Fusion. Proceedings of the National Academy of Sciences (PNAS). 102(14):5204-09, 2005
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