Ruanet V V, Kudriavtsev A M, Dadashev S Ia
Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow, 119991 Russia.
Genetika. 2001 Oct;37(10):1435-7.
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.
每个小麦品种都有其特有的醇溶蛋白谱。这使得在评估种子质量时，可以将贮藏蛋白的组成成分块用作遗传标记。然而，识别构成电泳谱的成分块是一项复杂的任务。为此，提出了人工神经网络（ANN）技术。基于实验数据，创建了一个教学数据库和多个测试数据库。结果表明，人工神经网络是一种用于解读硬粒小麦品种醇溶蛋白电泳谱的高效（效率高达100%）专家系统。
