Abstract:
Biological systems are examples of complex systems, which consist of several interacting
components. Understanding the behaviour of such systems requires
a multidisciplinary approach that encompasses biology, mathematics, computer
science, physiscs and chemistry. New research areas are emerging as the result
of this multidisciplinarity, such as bioinformatics, systems biology and computational
biology. Computer science plays an important role in the newly emerging
research areas by offerring techniques, algorithms, languages and software to solve
research problems efficiently. On the other hand, the efforts to solve these research
problems stimulate the development of new and better computer science
techniques, algorithms, languages and software.
This thesis describes our approach in modelling biological systems as a way to better
understand their complex behaviours. Our approach is based on the Calculi
of Looping Sequences, a class of formalisms originally developed to model biological
systems involving cells and their membrane-based structures. We choose
Stochastic CLS and Spatial CLS, two variants of the calculi that support quantitative
analysis of the model, and define an approach that support simulation,
statistical model-checking and visualisation as analysis techniques. Moreover, we
found out that this class of formalisms can be easily extended to model population
dynamics of animals, a kind of biological systems that does not involve
membrane-based structures.
