HPC applied to fluorescence fluctuation analysis: contributing to unravel hidden dynamical processes

S. NESMACHNOW, E. MOCSKOS, M. ORTEGA, J. ANGIOLINI, V. LEVI,

Conferencia; 5th International Supercomputing Conference; 2014

The fluorescence microscopy techniques and the capability of labeling proteins in the cellular environment with fluorescent tags constitute a significant breakthrough in the way the behavior of cells is studied. Fluorescence correlation spectroscopy and related techniques are extremely useful tools to measure quantitatively the motion of molecules in living cells. This article presents the application of scientific high performance computing techniques to complement the fluorescence fluctuation analysis using stochastic simulation. A parallel master-slave algorithm is introduced for processing the output data from microscopes studying cells expressing a fluorescent protein. Accurate speedup values are reported in the experimental analysis of the parallel master-slave implementation proposed over a cluster infrastructure.