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Front Neuroinform. 2008 Dec 19;2:6. doi: 10.3389/neuro.11.006.2008. eCollection 2008.

PyMOOSE: Interoperable Scripting in Python for MOOSE.

Author information

1
National Centre for Biological Sciences Bangalore, India.

Abstract

Python is emerging as a common scripting language for simulators. This opens up many possibilities for interoperability in the form of analysis, interfaces, and communications between simulators. We report the integration of Python scripting with the Multi-scale Object Oriented Simulation Environment (MOOSE). MOOSE is a general-purpose simulation system for compartmental neuronal models and for models of signaling pathways based on chemical kinetics. We show how the Python-scripting version of MOOSE, PyMOOSE, combines the power of a compiled simulator with the versatility and ease of use of Python. We illustrate this by using Python numerical libraries to analyze MOOSE output online, and by developing a GUI in Python/Qt for a MOOSE simulation. Finally, we build and run a composite neuronal/signaling model that uses both the NEURON and MOOSE numerical engines, and Python as a bridge between the two. Thus PyMOOSE has a high degree of interoperability with analysis routines, with graphical toolkits, and with other simulators.

KEYWORDS:

GENESIS; MOOSE; NEURON; Python; compartmental models; multi-scale models; simulators; systems biology

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