The Gillespie t-Leaping Method is an approximate algorithm that is faster than the exact Direct Method (DM) due to the progression of the simulation with larger time steps. However, the procedure to compute the time leap t is quite expensive. In this paper, we explore the acceleration of the t-Leaping Method using Graphics Processing Unit (GPUs) for ultra-large networks (w0:5e reaction channels...

The weighted stochastic simulation algorithm (wSSA) recently developed by Kuwahara and Mura and the refined wSSA proposed by Gillespie et al. based on the importance sampling technique open the door for efficient estimation of the probability of rare events in biochemical reaction systems. In this paper, we first apply the importance sampling technique to the next reaction method (NRM) of the s...

In this issue, Gillespie et al. (Gillespie et al. 2009. J. Cell Biol. doi:10.1083/jcb.200907037) demonstrate that the mitogen-activated protein kinase isoform p38-gamma plays a crucial role in blocking the premature differentiation of satellite cells, a skeletal muscle stem cell population. p38-gamma puts the brakes on skeletal muscle differentiation by promoting the association of the transcri...

The rate of clearance of radioactive xenon (‘33Xe) from a joint (St Onge, Dick, Bell and Boyle l968a ; Dick, Whaley, St Onge, Downie, Boyle, Nuki, Gillespie and Buchanan l970b) has been shown to reflect the degree of inflammatory involvement of the joint at the time of study, and has been used to measure synovial blood flow in the human knee (St Onge, Dick, Boyle, Jasani, Whaley, Pack and Bucha...

With an extensive career in cancer care, Catherine Gillespie is able to pull nursing and policy together.

The Stochastic Simulation Algorithm (SSA) is a milestone in the realm of stochastic modeling of biological systems, as it inspires all the current algorithms for stochastic simulation. Essentially, the SSA shows that under certain hypothesis the time to the next occurrence of a biochemical reaction is a random variable following a negative exponential distribution. Unfortunately, the hypothesis...

This paper describes preliminary results on the application of statistical model-checking to systems described with Stochastic CLS. Stochastic CLS is a formalism based on term rewriting that allows biomolecular systems to be described by taking into account their structure and by allowing very general events to be modelled. Statistical model-checking is an analysis technique that permits proper...

Stochastic models allow investigators to simulate reactions in a discrete way that can account for fluctuations that are otherwise ignored within a deterministic approach. Integrated particle system (IPS) models are a form of stochastic model that take spatial distributions, environmental factors, and agent migration into consideration. Unlike agent based models (ABM), IPS models only rely on a...

“Random” numbers (RNs) are of course only pseudo-random when generated on our computers: they are determined uniquely by the seed value and the algorithm for producing the next pseudorandom number from the last in the generated sequence. Care must be taken to use a high-quality RNG, and to always know what is going on with the seed (especially if you run multiple jobs on the cluster). RNs are v...