The cell cycle is a crucial event in biology that consists in
a series of repeated events allowing the cell to grow and duplicate
correctly. The study of the cell cycle involves the knowledge
of a large number of genes and networks of protein interactions:
thus a typical systems biology approach can be applied to study
this process in order to verify the impact that differently
regulated genes can have in normal cells and in cancer cells.
The key elements of systems biology studies are the models,which can be defined as abstract representations of biologicalcomponents and processes in order to mathematically describetheir structural and dynamical properties. The mathematicalmodelling of a biological process allows a systemic descriptionthat helps to highlight some features such as the emergent propertiesthat could be hidden when the analysis is performed only froma reductionist point of view.
Moreover, in modelling complex systems, a complete annotationof all the components is equally important to understand theinteraction mechanism inside the network. For this reason theintegration of data regarding the different components of eachmodel has high relevance in systems biology studies.
In this biological context we developed the cell cycle database,a data integration system that collects information about genes,proteins and models of different organisms’ cell cyclenetwork (Figure 1). We primary considered cell cycle informationfrom humans since we intend to create a resource to supportbiomedical studies in the context of cancer research. Then weextended the database content toward the budding yeast cellcycle because of the large number of models available for thisorganism. According to this choice, the data integration concernsall genes and proteins involved in the cell cycle models ofboth the budding yeast Saccharomyces cerevisiae and the Homosapiens. This information is taken from the most recent literatureand plays a crucial role to contextualize behaviour of eachcell cycle component.