Abstract
Molecular Biology produces a huge amount of data concerning the behavior of the single constituents of living organisms. Nevertheless, this reductionism view is not sufficient to gain a deep comprehension of how such components interact together at the system level, generating the set of complex behavior we observe in nature. This is the main motivation of the rising of one of the most interesting and recent applications of computer science: Computational Systems Biology, a new science integrating experimental activity and mathematical modeling in order to study the organization principles and the dynamic behavior of biological systems.
Among the formalisms that either have been applied to or have been inspired by biological systems there are automata based models, rewrite systems, and process calculi.
Here we consider a formalism based on term rewriting called Calculus of Looping Sequences (CLS) aimed to model chemical and biological systems. In order to quan-titatively simulate biological systems a stochastic extension of CLS has been de-veloped; it allows to express rule schemata with the simplicity of notation of term rewriting and has some semantic means which are common in process calculi.
In this thesis we carry out the study of the implementation of a stochastic sim-ulator for the CLS formalism. We propose an extension of Gillespie’s stochastic simulation algorithm that handles rule schemata with rate functions, and we present an efficient bottom–up, pre–processing based, CLS pattern matching algorithm.
A simulator implementing the ideas introduced in this thesis, has been developed in F#, a multi–paradigm programming language for .NET framework modeled on OCaml. Although F# is a research project, still under continuous development, it has a product quality performance. It merges seamlessly the object oriented, the functional and the imperative programming paradigms, allowing to exploit the performance, the portability and the tools of .NET framework.
