Python-based geometry preparation and simulation visualization toolkits for STEPS

Front Neuroinform. 2014 Apr 11:8:37. doi: 10.3389/fninf.2014.00037. eCollection 2014.

Abstract

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.

Keywords: Python; STEPS; Stochastic Simulation Algorithm; geometry preparation; simulation visualization; stochastic reaction diffusion simulation; tetrahedral mesh.