Projects

This is a list of complementary software projects to COPASI that have been written by members of our team. This includes two APIs for scripting languages, a tool for model composition and instructions for a particular approach to parameter estimation.

Currently maintained software:

• basiCO: A simplified python interface to COPASI. This is the preferred way to interface COPASI with Python programs as it provides a high level interface. Several software are now using basiCO. The link above is to the online documentation, the code repository is here and this software is now described in a peer review publication: Bergmann FT (2023) "BASICO: A simplified Python interface to COPASI" J Open Source Softw. 8:5553.
• CoRC: the COPASI R Connector. This is the preferred way to interface COPASI with programs written in the statistical language R. The link above is to the online documentation, the code repository is here and this software is described in a peer reviewed piblication: Förster J, Bergmann FT, Pahle J (2021) "CoRC - the COPASI R Connector" Bioinformatics 37:2778–2779.
• sbmodelr - a tool to replicate a COPASI/SBML model into a set of replicas. This is a python-based command line utility that reads a COPASI or SBML model to create a new model that is composed of several replicas of the original model. These base 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. This tool is useful to construct models of tissues based on a cell model, gene regulatory networks based on a single gene transcription model, and spiking neuronal networks based on a model of a single neuron, among other uses. The link above is the the online documentation, the code repository is here.
• Piecewise parameter fitting with COPASI. This is a strategy for piecewise parameter estimation in COPASI, particularly useful for stochastic models. The page describes examples of applying this method, which was originally described in this paper: Zimmer C (2012) "Parameter Estimation for Stochastic Models of Biochemical Reactions" J. Comp. Sci. Sys. Biol. 06:1. and the COPASI implementation in this one: Bergmann FT, Sahle S, Zimmer C (2016) "Piecewise parameter estimation for stochastic models in COPASI" Bioinformatics 32:1586–1588

Older software projects:

• JigCell Model Builder (1.0)
• JigCell Run Manager (JC-MSMB 2.0)
• JigCell Model Connector