Decision Tree Methods in Pharmaceutical Research

Title: Decision Tree Methods in Pharmaceutical Research

Volume: 6 Issue: 1

Author(s): Paul E. Blower and Kevin P. Cross

Affiliation:

Keywords: combinatorial chemistry, RECURSIVE PARTITIONING, pharmacophores, Sequential screening, SAR, Decision Forest (DF), Molconn-X topological descriptors

Abstract: Decision trees are among the most popular of the new statistical learning methods being used in the pharmaceutical industry for predicting quantitative structure-activity relationships. This article reviews applications of decision trees in drug discovery research and extensions to the basic algorithm using hybrid or ensemble methods that improve prediction accuracy.

Cite this article as:

Blower E. Paul and Cross P. Kevin, Decision Tree Methods in Pharmaceutical Research, Current Topics in Medicinal Chemistry 2006; 6 (1) . https://dx.doi.org/10.2174/156802606775193301