Encapsulated kinetics
Quantitative description of any kinetics or signaling is not thinkable without a system of differential equations. In order to find an optimal set of parameters for given set of equation, I have implemented a numerical integration of differential equations together with simulated annealing optimization for global fitting of experimental data. Awkward feature was that new set of equations had to be written in C/C++ code and application newly compiled. Fortunately brought Modelica, a modeling language that enables to define many various kinetic schemes in very convenient way and use them to find best model with optimal parameters. With its help we have created own module library and used it to describe some particular pathways in immune system. Final model could successfully interpret some immune processes, among them also inherent cycles. Fantastic feature of Modelica is that it enables to encapsulate parts of the system into sub-systems. They communicate through interfaces and can be hierarchically ordered in the frame of system to any arbitrary level. Such approach is very versatile and allows the creation of models even for very complex schemes.