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Using Recursive Partitioning Analysis to Evaluate Compound Selection Methods

  • S. Stanley Young
  • Douglas M. Hawkins
Protocol
Part of the Methods in Molecular Biology™ book series (MIMB, volume 275)

Abstract

The design and analysis of a screening set for high throughput screening is complex. We examine three statistical strategies for compound selection, random, clustering, and space-filling. We examine two types of chemical descriptors, BCUTs and principal components of Dragon Constitutional descriptors. Based on the predictive power of multiple tree recursive partitioning, we reached the following tentative conclusions. Random designs appear to be as good as clustering and space-filling designs. For analysis, BCUTs appear to be better than principal components scores based upon Constitutional Descriptors. We confirm previous results that model-based selection of compounds can lead to improved screening hit rates.

Key Words

Decision trees high throughput screening initial screening sets random recursive partitioning recursive partitioning sequential screening 

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Copyright information

© Humana Press Inc. 2004

Authors and Affiliations

  • S. Stanley Young
    • 1
  • Douglas M. Hawkins
    • 2
  1. 1.National Institute of Statistical SciencesResearch Triangle ParkNorth CarolinaUSA
  2. 2.School of StatisticsUniversity of MinnesotaMinneapolisUSA

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