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Recently, stochastic process algebras have been usedfor modeling biological systems, as they provide asimple, compositional language to define biologicalmodels. Classical process algebras, however, requireto express everything in terms of communications, alimiting restriction when structured informationneeds to be processed.In this book, we tackle this problem using a moregeneral language and programming it to deal with thedomain of interest. Specifically, we introduce astochastic extension (sCCP) of Concurrent ConstraintProgramming. It is precisely the use of constraintsthat gives flexibility and extendibility to thelanguage, together with the presence ofcontext-dependent stochastic rates. To prove this, weshow how sCCP can be used to model a wide range ofbiological systems, from biochemical networks to theprocess of folding of a protein, providing evidencethat the use of constraints simplifiesthe process of modeling and allows to incorporateexternal knowledge. Many analysis tools aredeveloped: stochastic simulation, model checking,ODE-based approximations. The book can be ofinterest to researchers working in the field ofcomputational systems biology.
