title: Data analysis of high-throughput screening results: application of multidomain clustering to the NCI anti-HIV data set.
abstract: The routine use of high-throughput screening (HTS) systems in the drug discovery process has resulted in an increasing need for fast, reliable analysis of massive amounts of data. A new automated multidomain clustering method that thoroughly analyzes screening data sets is used to examine both the active and the inactive compounds in a well-known, publicly available data set based on primary screening. Large and small compound sets that defined both chemical families and potential pharmacophore points were discovered. The detection of structure-activity relationships (SAR), aided by the unique classification method, is described in this article.
authors.affiliation: Bioreason, Inc., 150 Washington Avenue, Suite 220, Santa Fe, NM 87501, USA.
authors.forename: Susan Y
authors.initials: SY
authors.lastname: Tamura
authors.forename: Patricia A
authors.initials: PA
authors.lastname: Bacha
authors.forename: Heather S
authors.initials: HS
authors.lastname: Gruver
authors.forename: Ruth F
authors.initials: RF
authors.lastname: Nutt
mesh_terms: D000465:Algorithms; D019380:Anti-HIV Agents / Q000737:chemistry* / Q000145:classification; D020650:Combinatorial Chemistry Techniques; D016208:Databases, Factual; D009316:National Institutes of Health (U.S.); D021281:Quantitative Structure-Activity Relationship; D014481:United States
chemical_list: D019380:Anti-HIV Agents