title: Hybrid systems for virtual screening: interest of fuzzy clustering applied to olfaction.
abstract: Kohonen neural networks, also known as Self Organizing Map (SOM), offer a useful 2D representation of the compound distribution inside a large chemical database. This distribution results from the compound organization in a molecular diversity hyperspace derived from a large set of molecular descriptors. Fuzzy techniques based on the "concept of partial truth" reveal to be also a valuable tool for the direct exploitation of chemical databases or SOM. In such cases a fuzzy clustering algorithm is used. In this paper, a complete hybrid system, combining SOM and fuzzy clustering, is applied. As example, a series of olfactory compounds was selected. The complexity of such information is that a same compound may exhibit different odors. It is shown how fuzzy logic helps to have a better understanding of the organization of the compounds. These hybrid systems, using simultaneously SOM and fuzzy clustering, are foreseen as powerful tools for "virtual pre-screening".
authors.affiliation: Laboratory of Chemometrics and BioInformatics, University of Orléans, France.
authors.forename: F
authors.initials: F
authors.lastname: Ros
authors.forename: K
authors.initials: K
authors.lastname: Audouze
authors.forename: M
authors.initials: M
authors.lastname: Pintore
authors.forename: J R
authors.initials: JR
authors.lastname: Chrétien
mesh_terms: D017143:Fuzzy Logic; D016571:Neural Networks, Computer; D021281:Quantitative Structure-Activity Relationship; D012903:Smell / Q000502:physiology*; D012984:Software; D014584:User-Computer Interface