title: Feature selection in quantitative structure-activity relationships.
abstract: A key component of building quantitative structure-activity relationship (QSAR) models is the selection of an appropriate set of molecular features or descriptors. Feature selection can affect the accuracy, stability and interpretability of a model. There are thousands of molecular descriptors currently available, and the selection of an appropriate descriptor set for a particular model can be a daunting task. While there are no absolute rules for selecting appropriate sets of descriptors, a number of recent publications describe automated methods for identifying optimal feature sets. This review provides an overview of a number of the methods described in these publications.
authors.affiliation: Vertex Pharmaceuticals Inc, 130 Waverley St, Cambridge, MA 02139, USA. pat_walters@vrtx.com
authors.forename: W Patrick
authors.initials: WP
authors.lastname: Walters
authors.forename: Brain B
authors.initials: BB
authors.lastname: Goldman
mesh_terms: D000818:Animals; D015195:Drug Design; D006801:Humans; D008956:Models, Chemical; D008968:Molecular Conformation; D015394:Molecular Structure; D021281:Quantitative Structure-Activity Relationship