Type disciplines for systems biology

During the last years Computer Science and Biology are getting closer, helping and inspiring each other: for example, the Human Genome Project (HGP), the scientific research project with the goal of determining the sequence of chemical base pairs which make up DNA, would have been impossible without computer clusters and pattern recognition algorithms. On the other hand, Computer Scientists are studying vertebrate immune systems for applying their processes and solutions to antivirus softwares. A new interdisciplinary research field was born, the Natural Computing, encompassing both the application of Computer Science tools to Biology, and the use of biological solutions to computational issues. In the first sub-field we can find Systems Biology, a discipline that aims to study complex biological systems by means of computational models. Because of the complexity of biological behaviors, formalisms are usually designed ad-hoc for the biological topics of interest, or they need to be tuned by means of a long set of rules. In this Thesis we present a different approach: we define biological properties through type disciplines, leaving the formalisms as general as possible. From this starting point, we explore several applications of types in Systems Biology: the first one checks that biological compartments contain rules having certain features defined by the modeler, the second one allows to specify a set of elements required or avoided by other elements, the third one is an improvement of the previous one, the fourth one computes the rate of a stochastic transition by means of the types of the involved elements, and finally we end with a minimal Object Oriented Calculus for rewrite systems.