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 problems in nonlinear dynamics and
computational cell biology. A nice example 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
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 to the observed properties of cells. Bifurcation
theory is an especially useful tool for understanding the
'signal-response' characteristics of dividing cells. This approach is
generally applicable to any complex gene-protein network that regulates
some behavior of a living cell.
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