文档介绍：Artificial Intelligence
and Molecular( Biology
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Lawrence Hunter nn
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Joshua Lederberg nn
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Foreward
Joshua Lederberg
Historically rich in novel, subtle, often controversial ideas, Molecular Bi-
ology has lately e heir to a huge legacy of standardized data in the
form of polynucleotide and polypeptide sequences. Fred Sanger received
two, well deserved Nobel Prizes for his seminal role in developing the basic
technology needed for this reduction of core biological information to one
linear dimension. With the explosion of recorded information, biochemists
for the first time found it necessary to familiarize themselves with databases
and the algorithms needed to extract the correlations of records, and in turn
have put these to good use in the exploration of ic relationships,
and in the applied tasks of hunting genes and their often valuable products.
The formalization of this research challenge in the Human Genome Project
has generated a new impetus in datasets to be analyzed and the funds to sup-
port that research.
There are, then, good reasons why the management of DNA sequence
databases has been the main attractive force puter science relating to
molecular biology. Beyond the pragmatic virtues of access to enormous data,
the sequences present plications of representation; and the knowl-
edge-acquisition task requires hardly more than the enforcement of agreed
standards of deposit of sequence information in centralized, network-linked
archives.
The cell’s interpretation of sequences is embedded in a far more intricate
context than string-m