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.
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.
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.
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.