JSM 2004 - Toronto

Abstract #300312

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Activity Number: 361
Type: Invited
Date/Time: Wednesday, August 11, 2004 : 2:00 PM to 3:50 PM
Sponsor: Section on Physical and Engineering Sciences
Abstract - #300312
Title: Interpretability of Trees From High-throughput Screening Data
Author(s): Hugh Chipman*+ and Yan Yuan and William J. Welch
Companies: University of Waterloo and University of British Columbia
Address: Dept. of Statistics & Actuarial Science, Waterloo, ON, N2L 3G1, Canada
Keywords: high-throughput screening (HTS) ; sequential screening ; structure-activity relationship ; classification tree ; tree harvesting
Abstract:

Millions of compounds are available as potential drug candidates today, and high-throughput screening (HTS) is widely used to assay compounds for activity against a particular biological target. Often, classification trees are built to relate activity to variables characterizing chemical structure. These models are used to predict the activity of unscreened compounds, and hence select promising compounds to be screened in a sequential strategy. With a large dataset and a complex relationship between chemical structure and activity, a tree with hundreds of nodes may result. We describe a "tree harvesting" algorithm that simplifies a tree, making it easier to interpret. This facilitates the identification of interesting groups of compounds, to serve as diverse leads for drug optimization. Several data sets will be used to illustrate the methodology.

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