Computational Systems Biology with Constraints

Recently stochastic process algebras have been used for modeling biological systems as they provide a simple compositional language to define biological models. Classical process algebras however require to express everything in terms of communications a limiting restriction when structured information needs to be processed. In this book we tackle this problem using a more general language and programming it to deal with the domain of interest. Specifically we introduce a sto­chastic extension (sCCP) of Concurrent Constraint Programming. It is precisely the use of constraints that gives flexibility and extendibility to the language together with the presence of context-dependent stochastic rates. To prove this we show how sCCP can be used to model a wide range of biological systems from biochemical networks to the process of folding of a protein providing evidence that the use of constraints simplifies the process of modeling and allows to incorporate external knowledge. Many analysis tools are developed: stochastic simulation model checking ODE-based approximations. The book can be of interest to researchers working in the field of computational systems biology.