Literature DB >> 3959029

On the significance of clusters in the graphical display of structure-activity data.

J W McFarland, D J Gans.   

Abstract

A method is presented to evaluate the statistical significance of an apparently clustered group in the graphical display of structure-activity data. Two variations are described; each is implemented by means of a computer program. The first is applicable in situations with relatively small sets of compounds where a complete enumeration of all possible clusters can be accomplished reasonably on a high-speed electronic computer. The second is applicable in cases where such a calculation would be too time consuming. This latter variation uses random sampling of the set of all possible clusters. An application for each variation is given: for the smaller case a reevaluation of a study on aminotetralin and aminoindan monoamine oxidase inhibitors; for the larger case the discovery of some physical parameters that influence mutagenicity among some aminoacridine derivatives. It is proposed that this new technique be called cluster significance analysis (CSA).

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Year:  1986        PMID: 3959029     DOI: 10.1021/jm00154a014

Source DB:  PubMed          Journal:  J Med Chem        ISSN: 0022-2623            Impact factor:   7.446


  3 in total

1.  A genetic algorithm for the automated generation of small organic molecules: drug design using an evolutionary algorithm.

Authors:  D Douguet; E Thoreau; G Grassy
Journal:  J Comput Aided Mol Des       Date:  2000-07       Impact factor: 3.686

2.  Analysis of High-Dimensional Structure-Activity Screening Datasets Using the Optimal Bit String Tree.

Authors:  Ke Zhang; Jacqueline M Hughes-Oliver; S Stanley Young
Journal:  Technometrics       Date:  2013

3.  A model-based ensembling approach for developing QSARs.

Authors:  Qianyi Zhang; Jacqueline M Hughes-Oliver; Raymond T Ng
Journal:  J Chem Inf Model       Date:  2009-08       Impact factor: 4.956

  3 in total

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