Oscillatory regulation of hes1: Discrete stochastic delay modelling and simulation

Discrete stochastic simulations are a powerful tool for understanding the dynamics of chemical kinetics when there are small-to-moderate numbers of certain molecular species. In this paper we introduce delays into the stochastic simulation algorithm, thus mimicking delays associated with transcription and translation. We then show that this process may well explain more faithfully than continuous deterministic models the observed sustained oscillations in expression levels of hes1 mRNA and Hes1 protein.

Structure of saccharose-based carbon and transport of confined fluids: hybrid reverse Monte Carlo reconstruction and simulation studies

We present results of the reconstruction of a saccharose-based activated carbon (CS1000a) using hybrid reverse Monte Carlo (HRMC) simulation, recently proposed by Opletal et al. [1]. Interaction between carbon atoms in the simulation is modeled by an environment dependent interaction potential (EDIP) [2,3]. The reconstructed structure shows predominance of sp(2) over sp bonding, while a significant proportion of sp(3) hybrid bonding is also observed. We also calculated a ring distribution and geometrical pore size distribution of the model developed. The latter is compared with that obtained from argon adsorption at 87 K using our recently proposed characterization procedure [4], the finite wall thickness (FWT) model. Further, we determine self-diffusivities of argon and nitrogen in the constructed carbon as functions of loading. It is found that while there is a maximum in the diffusivity with respect to loading, as previously observed by Pikunic et al. [5], diffusivities in the present work are 10 times larger than those obtained in the prior work, consistent with the larger pore size as well as higher porosity of the activated saccharose carbon studied here.

Transport of simple fluids in nanopores: Theory and simulation

A theory is discussed of single-component transport in nanopores, recently developed by Bhatia and coworkers. The theory considers the oscillatory motion of molecules between diffuse wall collisions, arising from the fluid-wall interaction, along with superimposed viscous flow due to fluid-fluid interaction. The theory is tested against molecular dynamics simulations for hydrogen, methane, and carbon tetrafluoride flow in cylindrical nanopores in silica. Although exact at low densities, the theory performs well even at high densities, with the density dependency of the transport coefficient arising from viscous effects. Such viscous effects are reduced at high densities because of the large increase in viscosity, which explains the maximum in the transport coefficient with increase in density. Further, it is seen that in narrow pore sizes of less than two molecular diameters, where a complete monolayer cannot form on the surface, the mutual interference of molecules on opposite sides of the cross section can reduce the transport coefficient, and lead to a maximum in the transport coefficient with increasing density. The theory is also tested for the case of partially diffuse reflection and shows the viscous contribution to be negligible when the reflection is nearly specular. (c) 2005 American Institute of Chemical Engineers AIChE J, 52: 29-38, 2006.

Simulation of glassy state relaxations in polymers: A static analysis of methyl group and methoxy group rotation in poly(vinyl methyl ether)

We show that the simple quasi-static technique, also called the adiabatic mapping technique, can be used to determine the energetics of rotation of methyl and methoxy groups in amorphous poly(vinyl methyl ether) even though the latter process is too slow to be amenable to direct molecular dynamics simulation. For the methyl group rotation, we find that the mean and standard deviation of the simulated rotational barrier heights agree well with experimental data from quasi-elastic neutron scattering. In the case of the methoxy groups we find that just 4% of the groups contribute more than 90% of the observed dielectric relaxation strength. The groups which make the most contribution are those which, by virtue of their particular conformation and local environment, have two alternative positions of similar energy.

Parallel implementation of stochastic simulation for large scale cellular processes

Experimental and theoretical studies have shown the importance of stochastic processes in genetic regulatory networks and cellular processes. Cellular networks and genetic circuits often involve small numbers of key proteins such as transcriptional factors and signaling proteins. In recent years stochastic models have been used successfully for studying noise in biological pathways, and stochastic modelling of biological systems has become a very important research field in computational biology. One of the challenge problems in this field is the reduction of the huge computing time in stochastic simulations. Based on the system of the mitogen-activated protein kinase cascade that is activated by epidermal growth factor, this work give a parallel implementation by using OpenMP and parallelism across the simulation. Special attention is paid to the independence of the generated random numbers in parallel computing, that is a key criterion for the success of stochastic simulations. Numerical results indicate that parallel computers can be used as an efficient tool for simulating the dynamics of large-scale genetic regulatory networks and cellular processes