title: Recognising promoter sequences using an artificial immune system.
abstract: We have developed an artificial immune system (AIS) which is based on the human immune system. The AIS possesses an adaptive learning mechanism which enables antibodies to emerge which can be used for classification tasks. In this paper, we describe how the AIS has been used to evolve antibodies which can classify promoter containing and promoter negative DNA sequences. The DNA sequences used for teaching were 57 nucleotides in length and contained procaryotic promoters. The system classified previously unseen DNA sequences with an accuracy of approximately 90%.
authors.affiliation: Department of Computer Science, University of Wales, Aberystwyth, Dyfed, U.K.
authors.forename: D E
authors.initials: DE
authors.lastname: Cooke
authors.forename: J E
authors.initials: JE
authors.lastname: Hunt
mesh_terms: D000465:Algorithms; D000937:Antigen-Antibody Reactions; D000941:Antigens; D001402:B-Lymphocytes / Q000276:immunology; D001483:Base Sequence; D004247:DNA / Q000737:chemistry* / Q000235:genetics; D006801:Humans; D018448:Models, Immunological; D008962:Models, Theoretical; D008969:Molecular Sequence Data; D016571:Neural Networks, Computer; D011401:Promoter Regions, Genetic
chemical_list: D000941:Antigens; D004247:DNA