Modern technology provide us with large amounts of biological data. This
opens possibilities to study the large-scale organization and function
of a biological system. The information is, however, typically not
comprehensive enough to use the same tools for studying large-scale
systems (e.g. the metabolism) as small subsystems (e.g. the citric acid
cycle). I will discuss network theory in general, and how statistical
graph theory can be used to study the organization of metabolism.
Specifically I will talk about the role, definition and detection of
"currency metabolites" -- ubiquitous substances (like water, carbon
dioxide, ATP, etc.) that occur in a multitude of reactions.
