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HIV Gene Sequence Analysis for Drug Resistance Studies
Robert
Shafer, Medicine
Daphne
Koller, Computer Science
We have created the HIV RT and Protease Sequence
Database (HIVRT&PrDB) to represent, store,
and analyze the diverse forms of data underlying
drug resistance knowledge and have made these
data available online to researchers studying
HIV drug resistance and clinicians using HIV drug
resistance tests (http://hivdb.stanford.edu).
The database correlates sequence changes in RT
and protease to other forms of data including
antiviral treatment history, phenotypic (drug
susceptibility) data, and clinical outcome (the
virologic and immunologic response to a new treatment
regimen). The correlations in HIVRT&PrDB have
been used to develop a rules-based online expert
system (HIVdb) for helping physicians choose antiviral
drugs based on the RT and protease mutations in
a clinical virus sample.
To encode HIVdb, we have developed a programming
platform called an Algorithm Specification Interface
(ASI) that creates a uniform approach to encoding,
implementing, and comparing algorithms for HIV
genotypic interpretation. ASI consists of an XML
format for specifying an algorithm and a compiler
that transforms the XML into executable code.
Novel approaches have been developed to reduce
the high dimensionality of HIV sequence data.
Several machine learning projects have begun to
train HIVdb on clinical data sets as they are
collected and submitted to HIVRT&PrDB. |
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