sbmodelr - New modeling tool to create complex models

The COPASI team is happy to announce a new tool, called sbmodelr, which is intended to construct large models that are composed of repeating units. Essentially, you start with a base model and then tell sbmodelr to create a number of repeat units of that model, as well as which model entities interact between units.

sbmodelr is a python-based command line utility that reads a systems biology model, encoded in COPASI or SBML formats, to create a new model that is composed of several connected units that are replicates of the base model. These units may be organized as an arbitrarily connected network, a 2D rectangular grid, or a 3D cuboid array. Each unit contains a complete copy of the original model with all its species, reactions, compartments, events, and global quantities.

The new model can be a composition of the base according to:

• a 2D rectangular matrix of base units
• a 3D cuboid array of base units
• a number of units connected through an arbitrary network

Interactions between units in the new model can be:

• species being transported between units
• species acting as inhibitors/activators of the synthesis of other species (to make gene regulatory networks)
• diffusive coupling of explicit ODEs (“rate rules” in SBML)
• coupling of explicit ODEs through chemical synapse terms, appropriate for models representing membrane potentials

Practical uses of sbmodelr include:

• using a cell model to create a model of a tissue or organoid,
• use a gene transcription model to create a gene regulatory network
• use a neuron model (e.g. the Hodgkin-Huxley) to create a network of neurons

sbmodelr was written by Pedro Mendes in Python on top of basiCO. It is available immediately for installation using pypi (pip install sbmodelr). It is free and open source software under the Artistic License 2.0.