title: Pattern recognition display methods for the analysis of computed molecular properties.
abstract: Pattern recognition methods, particularly the 'unsupervised learning' techniques, are well suited for the preliminary analysis of the large data sets produced by computer chemistry. The use of linear and non-linear display methods for such exploratory analysis are exemplified with the aid of two data sets of biologically active molecules. Advantages and disadvantages of these techniques are discussed.
authors.affiliation: Department of Physical Sciences, Wellcome Research Laboratories, Beckenham, Kent, U.K.
authors.forename: B
authors.initials: B
authors.lastname: Hudson
authors.forename: D J
authors.initials: DJ
authors.lastname: Livingstone
authors.forename: E
authors.initials: E
authors.lastname: Rahr
mesh_terms: D003198:Computer Simulation; D015195:Drug Design; D008968:Molecular Conformation; D010363:Pattern Recognition, Automated; D011963:Receptors, GABA-A / Q000187:drug effects*; D012984:Software; D013329:Structure-Activity Relationship
chemical_list: D011963:Receptors, GABA-A