Multiscale Object Oriented Simulation Environment

Designed to simulate neural systems ranging from subcellular components and biochemical reactions to complex models of single neurons, circuits, and large networks.

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MOOSE Features

Modeling across domains: Supports both biochemistry and biophysics for integrated simulations.
Scalability: Built-in solvers with optimized data structures and algorithms models efficiently, yet maintain a biologically meaningful view for the user
Multiscale Capability: Enables seamless modeling and reaction-diffusion systems to multi-compartmental neuron models and large-scale biological neural networks
Model Switching: Easily toggles between deterministic and stochastic simulation modes for biochemical models.
Format Support: Handles multiple model formats, including SBML, NeuroML, and GENESIS(kkit, cell.p) Data can be saved in text, HDF5 based NSDF, or any other format compatible with numpy arrays
Rdesigneur: Simplifies the model-building process for faster creation and testing of integration models using a library of prototype components