The development of detailed, coherent, models of complex biological systems is recognized
as a key requirement for integrating the increasing amount of experimental data. In addition …

Investigating protein–protein interactions is crucial for understanding cellular biological
processes because proteins often function within molecular complexes rather than in …

To begin to elucidate the principles of intermolecular dynamics in the crowded environment
of cells, employing Brownian dynamics (BD) simulations, we examined possible mechanism …

We introduce the software package ReaDDy for simulation of detailed spatiotemporal
mechanisms of dynamical processes in the cell, based on reaction-diffusion dynamics with …

Spatial stochastic simulation is a valuable technique for studying reactions in biological
systems. With the availability of high‐performance computing (HPC), the method is poised to …

Interacting-particle reaction dynamics (iPRD) combines the simulation of dynamical
trajectories of interacting particles as in molecular dynamics (MD) simulations with reaction …

Stochastic expression of genes produces heterogeneity in clonal populations of bacteria
under identical conditions. We analyze and compare the behavior of the inducible lac …

In this paper, we describe our experiment developing an implementation of the Linpack
benchmark for TianHe-1, a petascale CPU/GPU supercomputer system, the largest GPU …

Molecular dynamics methodologies comprise a vital research tool for structural biology.
Molecular dynamics has benefited from technological advances in computing, such as …

Simulation of in vivo cellular processes with the reaction–diffusion master equation (RDME)
is a computationally expensive task. Our previous software enabled simulation of …