Bioinformatics Algorithms: Techniques and Applications

REFERENCES 457
lab may take months or even years so it is important not to be overly aggressive at
trimming processing speed at the cost of missing critical leads. It is more important
to find good lead compounds than it is to reduce the time of the query from a month
to a second.
Methods dealing with pairwise calculations may provide a solution to these problems
because they are independent of each other. Methods like parallel computing
and database arrangement can, therefore, be fully explored in the comparison applications.
Cluster analysis methods, for example, can be applied to obtain structural
clusters for organization in the chemical database. The clustered data can be organized
in the database in a distributed cluster way, a function which is provided by
most of the-state-of-art database systems. A cluster data arrangement can organize
the size of each of the participating databases in a manageable manner. For example,
all clusters can be logically connected, in a tree-structure fashion, based on their
structure features. This, in turn, allows the search routine to be performed quickly
via comparing the features. In a case of compound database searching, the features
of the query structure are first extracted. These features are then used as criteria for
searching through the cluster tree to find the cluster nodes that match the features.
Only those cluster data that meet the requirements are chosen for next step processing.
ACKNOWLEDGMENTS
This work was partially supported by NIH P20 GM065762-01A1, the Georgia
Research Alliance, and the Georgia Cancer Coalition. Dr. Harrison is Georgia Cancer
Coalition Distinguished Scholar.
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