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Journal of Biomolecular Screening
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Using Clustering Techniques to Improve Hit Selection in High-Throughput Screening

Andrei Gagarin

Laboratoire LaCIM, Université du Québec à Montréal, C.P. 8888, succursale Centre-Ville, Montréal (Québec), Canada, H3C 3P8

Vladimir Makarenkov

Département d’Informatique, Université du Québec à Montréal, C.P. 8888, succursale Centre-Ville, Montréal (Québec), Canada, H3C 3P8

Pablo Zentilli

Département d’Informatique, Université du Québec à Montréal, C.P. 8888, succursale Centre-Ville, Montréal (Québec), Canada, H3C 3P8

A typical modern high-throughput screening (HTS) operation consists of testing thousands of chemical compounds to select active ones for future detailed examination. The authors describe 3 clustering techniques that can be used to improve the selection of active compounds (i.e., hits). They are designed to identify quality hits in the observed HTS measurements. The considered clustering techniques were first tested on simulated data and then applied to analyze the assay inhibiting Escherichia coli dihydrofo-late reductase produced at the HTS laboratory of McMaster University.

Key Words: high-throughput screening • hit selection • nonhierarchical clustering • k-means partitioning • inside-cluster distance • intercluster distance

This version was published on December 1, 2006

Journal of Biomolecular Screening, Vol. 11, No. 8, 903-914 (2006)
DOI: 10.1177/1087057106293590
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