title: Calculation of substructural analysis weights using a genetic algorithm.
abstract: This work describes a genetic algorithm for the calculation of substructural analysis for use in ligand-based virtual screening. The algorithm is simple in concept and effective in operation, with simulated virtual screening experiments using the MDDR and WOMBAT data sets showing it to be superior to substructural analysis weights based on a naive Bayesian classifier.
authors.affiliation: Information School, University of Sheffield , 211 Portobello Street, Sheffield S1 4DP, United Kingdom.
authors.forename: John D
authors.initials: JD
authors.lastname: Holliday
authors.forename: Nor
authors.initials: N
authors.lastname: Sani
authors.forename: Peter
authors.initials: P
authors.lastname: Willett
mesh_terms: D000465:Algorithms; D019540:Area Under Curve; D001499:Bayes Theorem; D016861:Cyclooxygenase Inhibitors / Q000737:chemistry / Q000494:pharmacology; D062126:Databases, Chemical; D005823:Genetics; D057166:High-Throughput Screening Assays / Q000379:methods*; D008024:Ligands; D000069550:Machine Learning; D013329:Structure-Activity Relationship; D000092502:Renin Inhibitors
chemical_list: D016861:Cyclooxygenase Inhibitors; D008024:Ligands; D000092502:Renin Inhibitors