title: A study of learning splice sites of DNA sequence by neural networks.
abstract: To predict of splice sites in DNA sequence, we developed a neural network system with back propagation. This system has a flexible network definition language which can describe any network structure. Three types of neural network were defined using the system for the prediction of splice sites. The neural networks are trained by the arrangements of bases around the splice sites of DNA sequences. The results of simulation showed the excellent ability of the neural networks to predict splice sites by applying and testing the arrangements of DNA sequences. This system also were used to predict the effects of point mutations on the splicing of the IX factor gene which may cause hereditary disease.
authors.affiliation: Department of Information Science, Faculty of Engineering, Fukui University, Japan.
authors.forename: H
authors.initials: H
authors.lastname: Ogura
authors.forename: H
authors.initials: H
authors.lastname: Agata
authors.forename: M
authors.initials: M
authors.lastname: Xie
authors.forename: T
authors.initials: T
authors.lastname: Odaka
authors.forename: H
authors.initials: H
authors.lastname: Furutani
mesh_terms: D000465:Algorithms; D001483:Base Sequence; D003198:Computer Simulation; D005164:Factor IX / Q000235:genetics; D006801:Humans; D016571:Neural Networks, Computer; D009690:Nucleic Acid Conformation; D017354:Point Mutation; D012326:RNA Splicing / Q000235:genetics*; D017422:Sequence Analysis, DNA / Q000379:methods
chemical_list: D005164:Factor IX