The living cell is a dynamical system of molecular interactions. Most of the physiological characteristics of the cell (movement, growth and division etc.) are emergent properties of underlying molecular networks rather than determined by a single protein. These molecular networks are intrinsically dynamic and they dictate both the spatial and temporal behaviour of the cell. In order to understand the physiological consequences of these regulatory networks we use computational methods and mathematical models. Our models focus on the evolutionary-conserved eukaryotic cell cycle control system, addressing the following questions:
How do cells make decisions before they undergo major cell cycle transitions (e.g. before chromosome replication or segregation)?
How do they coordinate cell cycle progression with cell growth?
By using nonlinear differential equations we build accurate mathematical models that reproduce the physiological properties of normal cell cycle progression as well as the bizarre properties of mutant cells that have been studied. These models are teaching us that bistable switches underlie cell cycle decision-making, including cell size control, and they make these transitions irreversible. In order to find realistic kinetic parameter values for our dynamic models, we collaborate with numerous experimental groups who provide us with important quantitative data and qualitative observations. Our modelling work covers the cell cycle of eukaryotes from yeasts through early embryos and green algae to human cells.