An adaptive statistical test to detect non Brownian diffusion from particle trajectories

Abstract : Assessing the dynamics of particles inside live cell is of paramount interest to understand cell mechanisms. In this paper, we assume that the motions of particles follow a certain class of random process: the diffusion processes. Our contribution is to propose a statistical method able to classify the motion of the observed trajectories into three groups: confined, directed and free diffusion (namely Brownian motion). This method is an alternative to Mean Square Displacement (MSD) analysis. We assess our procedure on both simulations and real cases.
Type de document :
Communication dans un congrès
Workshop SSIAB - Spatial Statistics and Image Analysis in Biology, May 2016, Rennes, France. 〈http://www.lebesgue.fr/content/sem2016-SSIAB2016-program〉
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https://hal.inria.fr/hal-01416812
Contributeur : Charles Kervrann <>
Soumis le : mercredi 14 décembre 2016 - 19:20:49
Dernière modification le : mercredi 11 avril 2018 - 01:52:24

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  • HAL Id : hal-01416812, version 1

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Vincent Briane, Myriam Vimond, Charles Kervrann. An adaptive statistical test to detect non Brownian diffusion from particle trajectories. Workshop SSIAB - Spatial Statistics and Image Analysis in Biology, May 2016, Rennes, France. 〈http://www.lebesgue.fr/content/sem2016-SSIAB2016-program〉. 〈hal-01416812〉

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