Abstract
A graphical method is introduced for compound data mining and structure-activity relationship (SAR) data analysis that is based upon a canonical structural organization scheme and captures a compound-scaffold-skeleton hierarchy. The graph representation has a constant layout, integrates compound activity data, and provides direct access to SAR information. Characteristic SAR patterns that emerge from the graph are easily identified. The molecular hierarchy enables "forward-backward" analysis of compound data and reveals both global and local SAR patterns. For example, in heterogeneous data sets, compound series are immediately identified that convey interpretable SAR information in isolation or in the structural context of related series, which often define SAR pathways through data sets.
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