Abstract
This paper presents an exploratory study of a novel method for flexible 3-D similarity searching based on autocorrelation vectors and smoothed bounded distance matrices. Although the new approach is unable to outperform an existing 2-D similarity searching in terms of enrichment factors, it is able to retrieve different compounds at a given percentage of the hit-list and so may be a useful adjunct to other similarity searching methods.
Keywords
Similarity (geometry)AutocorrelationBounded functionComputer scienceDistance matrices in phylogenySimilitudeData miningPattern recognition (psychology)Information retrievalMathematicsArtificial intelligenceCombinatoricsStatisticsImage (mathematics)
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Publication Info
- Year
- 2006
- Type
- article
- Volume
- 46
- Issue
- 2
- Pages
- 615-619
- Citations
- 8
- Access
- Closed
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Cite This
Nicholas P. Rhodes,
David E. Clark,
Peter Willett
(2006).
Similarity Searching in Databases of Flexible 3D Structures Using Autocorrelation Vectors Derived from Smoothed Bounded Distance Matrices.
Journal of Chemical Information and Modeling
, 46
(2)
, 615-619.
https://doi.org/10.1021/ci0503863
Identifiers
- DOI
- 10.1021/ci0503863