title: Estimation of the optimal data base size for structure-activity analyses: the Salmonella mutagenicity data base.
abstract: In the present study, the effects of data base size on predictivity, informational content and structural overlap of derived Structure-Activity Relationship (SAR) models were investigated. It was found that indices of predictivity (i.e., sensitivity, specificity, and concordance between experimental and predicted results (OCP) increased with increasing size of the data base until the range is 300-400 chemicals, at which point they plateau. The greater the size of the data base, the greater the informational content of the model; however, the rate of this increase is no longer optimal when the size of the data base exceeds 400 chemicals.
authors.affiliation: Department of Environmental and Occupational Health, University of Pittsburgh, PA 15213, USA.
authors.forename: M
authors.initials: M
authors.lastname: Liu
authors.forename: N
authors.initials: N
authors.lastname: Sussman
authors.forename: G
authors.initials: G
authors.lastname: Klopman
authors.forename: H S
authors.initials: HS
authors.lastname: Rosenkranz
mesh_terms: D002273:Carcinogens / Q000737:chemistry; D007256:Information Systems; D009152:Mutagenicity Tests; D012044:Regression Analysis; D012475:Salmonella / Q000235:genetics / Q000378:metabolism; D013329:Structure-Activity Relationship
chemical_list: D002273:Carcinogens