Exact stochastic simulations of intra-cellular transport by mechanically coupled molecular motors

Abstract

Numerous processes in live cells depend on active, motor-driven transport of cargo and organelles along the filaments of the cytoskeleton. Understanding the resulting dynamics and the underlying biophysical and biochemical processes critically depends on computational models of intra-cellular transport. A number of motorcargo models have hence been developed to reproduce experimentally observed transport dynamics on various levels of detail. Computer simulations of these models have so far exclusively relied on approximate time-discretization methods. Using a consensus motorcargo model that unites several existing models from the literature we demonstrate that this simulation approach is not correct. The numerical errors do not vanish even for arbitrarily small time steps, rendering the algorithm inconsistent. We propose a novel exact simulation algorithm for intra-cellular transport models that is also computationally more efficient than the approximate one. Furthermore, we introduce a robust way of analyzing the different time scales in the model dynamics using velocity autocorrelation functions. AbstractNumerous processes in live cells depend on active, motor-driven transport of cargo and organelles along the filaments of the cytoskeleton. Understanding the resulting dynamics and the underlying biophysical and biochemical processes critically depends on computational models of intra-cellular transport. A number of motor-cargo models have hence been developed to reproduce experimentally observed transport dynamics on various levels of detail. Computer simulations of these models have so far exclusively relied on approximate time-discretization methods. Using a consensus motor-cargo model that unites several existing models from the literature we demonstrate that this simulation approach is not correct. The numerical errors do not vanish even for arbitrarily small time steps, rendering the algorithm inconsistent. We propose a novel exact simulation algorithm for intra-cellular transport models that is also computationally more efficient than the approximate one. Furthermore, we introduce a robust way of analyzing the different time scales in the model dynamics using velocity autocorrelation functions.

Framework for determining airport daily departure and arrival delay thresholds: statistical modelling approach

“…Variations of levels of significance for parameters of delay were detected at different delay thresholds, thus generating different numbers of significant parameters. For example, in both Tables 4 and 5 ; sub-table (d) presented the worst levels of parameter sensitivity with the least number of significant variables while sub-table (b) provided more stable models in both cases (Wesonga and Nabugoomu 2014 ; Helmuth et al 2011 ).…”

Exciting Times in Computational Science

“…In keeping with our objectives for JoCS, this issue covers a broad range of computational science [1][2][3][4][5][6][7][8][9]. The featured papers include discussions of novel topics such as stochastic simulations of intra-cellular transport, new approaches to coupled systems in computational fluid dynamics, the emergence of geographical patters of electoral preferences and the optimisation of climate model parameters.…”