Who can find such solutions with all these little pieces?

Anyone with a keen interest in solving puzzles and ready access to a PC, an Excel spreadsheet, and a copy of the Enterprise Biology Software can become a player. 

The software package includes an information infrastructure, one that uses the biology literature as a stepping-stone to discovery.  It enjoys simplicity of design and application, readily accessible - even to the beginner.  The secret of its success is that it begins at the beginning, with the data. 

Biology and its literature derive from four basic data elements (volume, surface, length, and number) that form three basic data types - concentrations, amounts, and proportions.  We have two options.  We can either use these data types separately (reductionism) or as a connected set (connectionism).  Our choice determines our playing field, the game, and the outcome.    

Notice that the information infrastructure asks and answers - two key questions.  What game is biology playing and how can we play the same game?  Biology plays the complexity game, which we can play as well because an information infrastructure allows us to manage complexity effectively.  By operating within the framework of this infrastructure, biology can behave as a quantitative science - complete with variables, equations, rules, and principles.

Complexity, of course, comes in two forms: natural and man-made.  The man-made variety typically comes from one or more of the following: poor sampling, specimen preparation, semiquantitative approaches, an inability to detect biological changes accurately, and reductionism (disconnected data).  The information infrastructure minimizes these man-made complexities by enforcing unbiased sampling, applying robust approaches, minimizing bias and animal variation, and treating the three data types as a connected set.  In effect, variables guided by equations and rules become a key component of the game plan.