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HIVA is the HIV infection
database
The task of HIVA is to predict which compounds are active against
the AIDS HIV infection. The original data has 3 classes (active, moderately
active, and inactive). We brought it back to a two-class classification problem
(active vs. inactive), but we provide the original labels for the "prior knowledge
track". The compounds are represented by their 3d molecular structure for
the “prior knowledge” track. For the “agnostic track” we represented the
data as 2000 sparse binary input variables. The variables represent properties
of the molecule inferred from its structure. The problem is therefore to relate
structure to activity (a QSAR=quantitative structure-activity relationship
problem) to screen new compounds before actually testing them (a HTS=high-throughput
screening problem.)
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