Abstract
MotivationCOPASI is an open source software package for constructing, simulating and analyzing dynamic models of biochemical networks. COPASI is primarily intended to be used with a graphical user interface but often it is desirable to be able to access COPASI features programmatically, with a high level interface.ResultsPyCoTools is a Python package aimed at providing a high level interface to COPASI tasks with an emphasis on model calibration. PyCoTools enables the construction of COPASI models and the execution of a subset of COPASI tasks including time courses, parameter scans and parameter estimations. Additional ‘composite’ tasks which use COPASI tasks as building blocks are available for increasing parameter estimation throughput, performing identifiability analysis and performing model selection. PyCoTools supports exploratory data analysis on parameter estimation data to assist with troubleshooting model calibrations. We demonstrate PyCoTools by posing a model selection problem designed to show case PyCoTools within a realistic scenario. The aim of the model selection problem is to test the feasibility of three alternative hypotheses in explaining experimental data derived from neonatal dermal fibroblasts in response to TGF-β over time. PyCoTools is used to critically analyze the parameter estimations and propose strategies for model improvement.Availability and implementationPyCoTools can be downloaded from the Python Package Index (PyPI) using the command ’pip install pycotools’ or directly from GitHub (https://github.com/CiaranWelsh/pycotools). Documentation at http://pycotools.readthedocs.io.Supplementary information Supplementary data are available at Bioinformatics online.
Highlights
In biology, systems modelling is used to reproduce the dynamics of a biochemical network of molecular interactions with a mathematical model
The PyCoTools package is comprised of three main modules: ‘model’, ‘tasks’ and ‘viz’
PyCoTools wraps functions from Tellurium (Choi et al, 2016) and command line COPASI to convert between Antimony, SBML and COPASI models, thereby facilitating the transition between environments
Summary
Systems modelling is used to reproduce the dynamics of a biochemical network of molecular interactions with a mathematical model It has proved useful in the study of cell signalling systems such as NF-jB (Adamson et al, 2016; Ashall et al, 2009; Nelson et al, 2004), mTOR (Dalle Pezze et al, 2012, 2016), p53 (Purvis et al, 2012; Sun et al, 2011) and TGF-b (Schmierer et al, 2008; Vilar et al, 2006; Wang et al, 2014; Zi and Klipp, 2007; Zi et al, 2014). ODE models are prevalent in systems biology because they are well-suited for predicting system dynamics and because many computational tools have been developed
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