100 years after Smoluchowski: stochastic processes in cell biology

Research paper by David Holcman, Zeev Schuss

Indexed on: 26 Dec '16Published on: 26 Dec '16Published in: arXiv - Physics - Data Analysis; Statistics and Probability


100 years after Smoluchowski introduces his approach to stochastic processes, they are now at the basis of mathematical and physical modeling in cellular biology: they are used for example to analyse and to extract features from large number (tens of thousands) of single molecular trajectories or to study the diffusive motion of molecules, proteins or receptors. Stochastic modeling is a new step in large data analysis that serves extracting cell biology concepts. We review here the Smoluchowski's approach to stochastic processes and provide several applications for coarse-graining diffusion, studying polymer models for understanding nuclear organization and finally, we discuss the stochastic jump dynamics of telomeres across cell division and stochastic gene regulation.