Reaction systems were proposed in  as a formal framework with underlying rationale adopted from the biochemical reactions. The interaction between individual biochemical reactions takes place through their influence on each other, and this influence happens through the basic mechanisms of facilitation and inhibition.
A reaction is modeled as a triplet: a set of reactants, a set of inhibitors, and a set of products. A reaction can take place in a given state if all its reactants are present in that state and none of its inhibitors; when triggered, the reaction creates its products. Two major assumptions in reaction systems set them apart from standard methods for biomodeling:
- The threshold assumption: if a resource is present, then it is present in a “sufficient amount” and it will not cause any conflict between several reactions needing that resource.
- The no permanency assumption: an entity will vanish from the current state unless it is produced by one of the reactions enabled in that state.
The evolution of reaction systems is given by interactive processes. The following figure shows an example of an interactive process. The reaction system starts on the initial context C0, then another context C1 is added to the first result D1, etc.
We focus in this project on developing tools for building reaction-system biomodels and analyzing their dynamic behavior through interactive processes. We aim to deepen the investigation of reaction systems from an applied point of view and to confirm their feasibility and expressive power as a modeling framework in multidisciplinary applications. We are interested in particular in model checking for the reaction systems framework. Some of our works on this topic can be found in  and . Some recent surveys can be found at [4-6].
Team: Ion Petre, Cristian Gratie, Sepinoud Azimi, Bogdan Iancu, Sergiu Ivanov.
 Sepinoud Azimi, Bogdan Iancu, Ion Petre, Reaction System Models for the Heat Shock Response. Fundamenta Informaticae 131, 1–14 , 2014.
 Sepinoud Azimi, Exact String Matching with Reaction Systems. TUCS Technical Reports 1104, TUCS, 2014.
 A. Ehrenfeucht and G. Rozenberg. Reaction systems. Fundamenta Informaticae, 75(1):263–280, 2007.
 A. Ehrenfeucht, M. Main, G. Rozenberg, A.T. Brown. Stability and Chaos in Reaction Systems. International Journal of Foundations of Computer Science, 23:1173-1184, 2012. doi:10.1142/S0129054112500177
 A. Ehrenfeucht, M. Main, G. Rozenberg. Functions defined by reaction systems. International Journal of Foundations of Computer Science, 22:167-178, 2011.
 A. Ehrenfeucht, M. Main, G. Rozenberg. Combinatorics of life and death for reaction systems. International Journal of Foundations of Computer Science, 21:345-356, 2010.