title: Application of neural networks in structure-activity relationships.
abstract: Methodology and application of artificial neural networks in structure-activity relationships are reviewed focusing on the most frequently used three-layer feedforward back-propagation procedure. Two applications of neural networks are presented and a comparison of the performance with those of CoMFA and a classical QSAR analysis is also discussed.
authors.affiliation: EGIS Pharmaceuticals Ltd., Budapest, Hungary.
authors.forename: I
authors.initials: I
authors.lastname: Kövesdi
authors.forename: M F
authors.initials: MF
authors.lastname: Dominguez-Rodriguez
authors.forename: L
authors.initials: L
authors.lastname: Orfi
authors.forename: G
authors.initials: G
authors.lastname: Náray-Szabó
authors.forename: A
authors.initials: A
authors.lastname: Varró
authors.forename: J G
authors.initials: JG
authors.lastname: Papp
authors.forename: P
authors.initials: P
authors.lastname: Mátyus
mesh_terms: D015195:Drug Design; D016571:Neural Networks, Computer; D013329:Structure-Activity Relationship