WELCOME
Welcome to
the new software package. The Enterprise Biology Software Project
has reached its first ten-year milepost and the report uses this
occasion to look back and then ahead.
Two
overarching themes - complexity and
phenotypes – have become central to the ongoing effort.
Although we already know many details about how the genome codes for the parts making up
the phenotype, we are only beginning to understand the extent to
which the phenotype defines and is defined by complexity.
Conventional wisdom often assumes that understanding the
genome will allow us to understand biology and to revolutionize
modern medicine. Surprisingly little attention, however, is being
given to understanding the underlying principles of phenotypes or to
those of biological complexity. Numerous articles - even in the
popular press - repeatedly remind us that the benefits of the Human
Genome Project continue to fall far short of expectations. Indeed, the
major diseases do not appear to be in decline. On the contrary,
many are reporting considerable gains in recent years. Is this
telling us that we are missing something important?
What we
need, perhaps, is a new role model, one with real-world skills and many
years of experience. Take biology, for instance. It runs its
business with great success as a grand enterprise, paying very
careful attention to what happens in its genome and
in all the hierarchical parts of its phenotype (i.e., its phenome). If
biology has learned how to solve its problems by taking the trouble
to work out the complex relationships of genome to phenome, how can
we justify devoting so much of our time and effort to just the
genome? Have we somehow forgotten that the genome is just the
opening chapter of a story that is - for the most part - about
phenotypes.
Biology
has figured out how to turn something simple – genes – into
something complex – phenotypes. It performs this astonishing task
because it can build, maintain, and relentlessly fine-tune a massive
information infrastructure. If our goal is to become as clever as
biology, then how can we do it without a comparable infrastructure?
Is this the key point that we seem to be missing? The current
report finds such questions engaging and considers what we might
learn from phenotypes by merely simplifying their complexity.
The
software package offers:
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A
progress report.
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A
complete copy of the Information Infrastructure.
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A new
digital libraries for organism codes based on triplets.
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Worked
examples.
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Recommendations
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Updates to programs and databases.
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