The fundamental goal of molecular cell biology is to understand cell physiology in terms of the information encoded in the cell's genome. In principle, we know how this information is translated into functional proteins that carry out most of the interesting chores in a living cell. But to make a firm connection between molecular events and cell behavior involves many challenging computational problems at every step along the way. The early steps – sequence analysis, protein folding, molecular dynamics, metabolic control theory – are well established branches of biochemistry. But the 'last step', from networks of regulatory proteins to the physiological responses of a cell to its environment, is an especially challenging problem that has received little attention so far. Accurate and effective computational methods for deriving cell behavior from molecular wiring diagrams are crucial to future progress in understanding living cells and in modifying cell physiology for medical and technological purposes.

A nice example of this challenge is the cell cycle: the sequence of events by which a growing cell duplicates all its components and partitions them more-or-less evenly between two daughter cells. The cell cycle is fundamental to all processes of biological growth, development and reproduction, and hence plays a central role in such important processes as carcinogenesis, wound healing, and tissue engineering. The molecular mechanism that controls DNA synthesis and nuclear division is so complex that its behavior cannot be understood by casual, hand waving arguments. By translating this mechanism into differential equations, we can analyze and simulate the behavior of the control system, comparing model predictions with the observed properties of cells. Theoretical models also provide new ways to look at the dynamics of cell cycle regulation. This approach is generally applicable to any complex gene-protein network that regulates some behavior of a living cell.