           Why?     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 straightforward exercise.   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?                                                    Southwest      Copyright © 2001 - 2016 Robert P. Bolender and Licensors | Home | Contact | Site Map