title: Structure-activity analyzed by pattern recognition: the asymmetric case.
abstract: In classification studies in which pattern-recognition methods are used to distinguish active compounds from inactive ones, a type of data structure which we call "asymmetric" can be observed. This type of data structure can be quite common and its occurrence can have a profound effect on the classification analysis outcome. The origin of asymmetric data structure and a strategy or obtaining meaningful classification results when it is observed are discussed and illustrated with an example of active and inactive antimalarial quinones.
mesh_terms: D000962:Antimalarials; D008962:Models, Theoretical; D009285:Naphthoquinones / Q000494:pharmacology; D010363:Pattern Recognition, Automated; D004364:Pharmaceutical Preparations / Q000145:classification; D010962:Plasmodium berghei / Q000187:drug effects; D013329:Structure-Activity Relationship
chemical_list: D000962:Antimalarials; D009285:Naphthoquinones; D004364:Pharmaceutical Preparations