If biology exists as a rule-based
system, then why not treat biology as a mathematical problem?
We begin by
setting up the problem – in a way not unlike what we did in our
introductory math courses. Recall that this consisted of
first applying an algorithm that we deduced from our understanding of the problem and
then plugged in the data to get the solution. But, how
can we apply this to biology?
In biology, complexity – in a mathematical setting –
defines the problem as a function of a complex data set. Solving
such a complexity seems to require data that capture biological
parts, connections, and rules - simultaneously. Given such
data, biology becomes surprisingly accommodating in that it will set up the problem for us; all we have to do is know where
to look, make the calculations,
and explain the results. Indeed,
solving biology as a complexity turns out to be a surprisingly
In practice, this process of complex problem solving
consists of running published data through an information
infrastructure designed specifically to set up and solve
complexities. We begin by first setting up a complexity
parallel to the one of biology and then stand back and let biology
solve the problem for us. What could be simpler?