Abstract

Being a multi-disciplinary field of research, Systems Biology struggle to have a common view and a common vocabulary, and inevitably people coming from different backgrounds see and care about different aspects. Scientists have to work hard to comprehend each other and to take advantage of each others work, but on the other hand they can provide unexpected and beautiful new insight to the problems we have to face, enabling cross-fertilization among different disciplines. However, Systems Biology scientists all share one main goal, in the end: comprehend how a system as complex as a living creature can work and exists. Once we really understand how and why a biological system works, we can answer other important questions: can we fix it when it breaks down; can we enhance it and make it more resistant, correct its flaws; can we reproduce its behaviour and take it as inspiration for new works of engineering; can we copy it to make our everyday work easier and our human-created systems more reliable. The contribution of this thesis is to push ahead the current state of art in different areas of information technology and computer science as applied to systems biology, in a way that could lead, one day, to the understanding of a whole, complex biological system. In particular, this thesis builds upon the current state of art of different disciplines, like programming languages theory and implementation, parallel computing, software engineering and visualization. Work done in these areas is applied to Systems Biology, in the effort to scale up the dimension of the problems that is possible to tackle with current tools and techniques.