COPASI – Complex Pathway Simulator

A few weeks ago I attended a modelling and simulation Copasi workshop run at the MIB by Professor Pedro Mendes. I had attempted to blog about it previously but lab work got in the way.

The workshop was a 3 day event detailing all aspects of the Copasi software, much of which can be found in chapter 2 of the “methods in molecular biology” (2009) Volume 500. 1-43, available as a preview here. (There is also a publication associated with Copasi by Hoops et al. (2006) Bioinformatics 22, 3067-74).  I’m no mathematician, so my description of Copasi wont be the most accurate!  For me, Copasi is a graphical user interface into the world of mathematical modelling providing an immediate step up in to the capabilities of Matlab and Mathematica armed scientists without requiring particularly large amounts of experience of programming or modelling.  The software forms a fundamental toolkit of everything a biologist, or mathematician/computer scientist, needs to build models of systems of reactions and run simulations on them.  You can enter your reactions using symbolic algebra equations such as those found in many standard biochemistry textbooks, or directly as systems of ODE’s so it is familiar to both wet and dry scientists.  A large number of standard enzyme kinetics equations are available when creating your model such as Michaelies Menten types and hill equations as well as all kinds of inhibitor-substrate relationships,  and the ability to enter your own.

At its most basic you can input reactions between species of compounds using symbolic algebra and then create plots of the behaviour or those species as they react together in your system over time. You can quickly gain a grasp however of the underlying power of Copasi when you begin to make more sophisticated enquiries of your system.  Using the graphical interface you are able to perform a range of systems biology / modelling techniques from finding steady states, to metabolic control and sensitivity analysis.  The real power behind Copasi comes from the advanced features however, particularly the parameter scan which is currently not available in any of the equivalent simulation tools and would require substantial programming experience in Matlab or Mathematica. The parameter scan enables you to set a certain parameter at a range of values and repeatedly run the simulation, plotting the output from each iteration.  This, for me was a hugely powerful tool as you can test your model under a range of initial conditions, in a high throughput manner.

Copasi is also capable of performing parameter estimation, which allows you to input laboratory data into your model as parameter values and then fit your model parameter values to the data to “reduce the distance” between your model and your observations and reproduce in vivo representative behaviour.  In addition, there are a number of optimization algorithms built into Copasi that can optimize your model towards an objective function, or find conditions under which the model behaves in some particular way.  There are a wide range of algorithms pre-programmed into Copasi for these tasks including evolutionary programming, genetic algorithms, particle swarms, Praxis, Hooke and Jeeves and more.  For the even braver modellers, Copasi can be used in conjunction with Gepasi, an older relative of Copasi that can be used to run multiple simulations simultaneously.  For example, you can have multiple copies of a model representing a culture of interacting cells or systems and run multiple simulations on multiple interacting models!

Models can be imported and exported in xml and sbml format and ODE’s can be exported in LaTeX and MathML formats for transfer between different applications.  Models from biomodels.net can be imported directly into Copasi and there is a feature to update model details from the Miriam database.  There is also a command line version of Copasi that enables high throughput “automated” modelling processes to be run.  The Copasi group is also working on a web interface enabling scientists to access the software through a web browser interface.

The comprehensive tool set available in Copasi provides a hugely powerful tool for the budding systems biologists to immerse themselves in the field of mathematical modelling and perform some fairly rigorous and comprehensive modelling techniques without prior experience of complex mathematical programming.  It can also produce data for the biologist with a minimum of mathematical knowledge, providing some interesting incites for experimental hypothesis generation.

Copasi is available as open-source, and free for academic research from http://www.copasi.org,  and is under continuous development by a core team of programmers as well as a community of users interacting through an active forum.  The software is available for Windows, Mac, and Linux.  If you’re currently wresting with Matlab or modelling in general,  I would recommend Copasi as an excellent starting point to dive into the sometimes intractable world of mathematical modelling, particularly coming from a biological background.