title: [Use of artificial neuronal nets in automation of analysis and genetic identification of electrophoretic spectra of gliadin from durum wheat].
abstract: Each wheat cultivar has a characteristic spectrum of gliadins. This makes it possible to use blocks of the components of reserve proteins as genetic markers when estimating seed quality. However, identification of the blocks that constitute the electrophoretic spectrum is a complicated task. For this purpose artificial neural network (ANN) technology is proposed. Based on experimental data, a teaching database and testing databases have been created. ANN was shown to be highly efficient (efficiency up to 100%) expert system for deciphering the electrophoretic spectra of gliadins of durum wheat cultivars.
authors.affiliation: Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow, 119991 Russia.
authors.forename: V V
authors.initials: VV
authors.lastname: Ruanet
authors.forename: A M
authors.initials: AM
authors.lastname: Kudriavtsev
authors.forename: S Ia
authors.initials: SIa
authors.lastname: Dadashev
mesh_terms: D001331:Automation; D004586:Electrophoresis; D005903:Gliadin / Q000235:genetics*; D016571:Neural Networks, Computer; D014908:Triticum / Q000235:genetics*
chemical_list: D005903:Gliadin
vernacular_title: Ispol'zovanie iskusstvennykh neĭronnykh seteĭ pri avtomatizatsii analiza i geneticheskoĭ rasshifrovke élektroforeticheskikh spektrov gliadina tverdoĭ pshenitsy.