Computational modelling of molecular and cellular biology: new perspectives in tissue engineering

The importance of computational models in systems biology has grown in recent years, as their ability to understand, predict and manipulate biological systems has been successfully demonstrated in many cases. Modelling means representing an abstraction of the biological/clinical system in a simpler but still meaningful way with respect to the goal of the study. For this reason, modelling requires a balance between complexity and accuracy. The appropriate methodology to define and analyse the model is based on a fine selection considering the model goals, the experimental data and biological knowledge available for the phenomena under study.

A model should shed light on the system under study and offer a deeper understanding of its behaviour. It should then help users to formulate new experimental hypotheses around the mechanisms that generated the observed phenomena, or to predict new phenomena that were not used in the process of model building.