STEPS is a stochastic reaction-diffusion simulation engine that implements a spatial extension of Gillespie’s Stochastic Simulation Algorithm (SSA) in complex tetrahedral geometries. An extensive Python-based interface is provided to STEPS so that it can interact with the large number of scientific packages in Python. However, a gap existed between the interfaces of these packages and the STEPS user interface, where supporting toolkits could reduce the amount of scripting required for research projects. This paper introduces two new supporting toolkits that support geometry preparation and visualization for STEPS simulations
Transition path sampling techniques allow molecular dynamics simulations of complex systems to focus...
Spatial stochastic reaction-diffusion simulation has been recognized as an essential modeling tool i...
The popularization of inexpensive 3D scanning, 3D printing, 3D publishing and AR/VR display technolo...
GillesPy is an open-source Python package for model construction and simulation of stochastic bioche...
Abstract Background Experiments in silico using stochastic reaction-diffusion models have emerged as...
Abstract—Stochastic simulations of biological systems vary widely in scope from reaction modules, to...
Though the years the efficiency of Gillespie SSA [1] has been improved by different approaches. Many...
Parallelization is vital in the future of spatial stochastic simulation and an important component o...
We present the Stochastic Simulator Compiler (SSC), a tool for exact stochastic simulations of well-...
Interacting Particle Systems (IPSs) are used to model spatio-temporal stochastic systems in many dis...
Motivation: The importance of stochasticity in biological systems is becoming increasingly recognize...
This project is described in: Three-color single-molecule imaging reveals conformational dynamics of...
I will present two programs that facilitate computational exploration of reaction-diffusion patterns...
One and two dimension diffusion-reaction simulation with a pre-nucleation model for the formation of...
This python code allows the user to obtain the information needed to run a Step Selection Function. ...
Transition path sampling techniques allow molecular dynamics simulations of complex systems to focus...
Spatial stochastic reaction-diffusion simulation has been recognized as an essential modeling tool i...
The popularization of inexpensive 3D scanning, 3D printing, 3D publishing and AR/VR display technolo...
GillesPy is an open-source Python package for model construction and simulation of stochastic bioche...
Abstract Background Experiments in silico using stochastic reaction-diffusion models have emerged as...
Abstract—Stochastic simulations of biological systems vary widely in scope from reaction modules, to...
Though the years the efficiency of Gillespie SSA [1] has been improved by different approaches. Many...
Parallelization is vital in the future of spatial stochastic simulation and an important component o...
We present the Stochastic Simulator Compiler (SSC), a tool for exact stochastic simulations of well-...
Interacting Particle Systems (IPSs) are used to model spatio-temporal stochastic systems in many dis...
Motivation: The importance of stochasticity in biological systems is becoming increasingly recognize...
This project is described in: Three-color single-molecule imaging reveals conformational dynamics of...
I will present two programs that facilitate computational exploration of reaction-diffusion patterns...
One and two dimension diffusion-reaction simulation with a pre-nucleation model for the formation of...
This python code allows the user to obtain the information needed to run a Step Selection Function. ...
Transition path sampling techniques allow molecular dynamics simulations of complex systems to focus...
Spatial stochastic reaction-diffusion simulation has been recognized as an essential modeling tool i...
The popularization of inexpensive 3D scanning, 3D printing, 3D publishing and AR/VR display technolo...