【摘要】 该文将人工神经网络方法用于DNA分类。首先应用概率统计的方法对 2 0个已知类别的人工DNA序列进行特征提取 ,形成DNA序列的特征向量 ,并将之作为样本输入BP神经网络进行学习。采用MATLAB软件包中的神经网络工具箱中的反向传播算法来训练神经网络。构造了两个三层BP神经网络 ,将提取的DNA特征向量集作为样本分别输入这两个网络进行学习。通过训练后 ,将 2 0个未分类的人工序列样本和 182个自然序列样本提取特征向量并输入两个网络进行分类。结果表明 :分类方法能够以很高的正确率和精度对DNA进行分类 ,将人工神经网络用于DNA序列分类是完全可行的。更多还原

【Abstract】 This paper presents a method applying artificial neural network to DNA clustering problem. First we use the probability statistics method to extract the characters from the artificial DNA sequences whose categories are known. Thu s we can get the character vectors of the DNA sequences and input them as sample s into BP neuron NN for learning. We employ the BP(back propagation) algorithm t o train NN by use of the Neural Network Toolbox in MATLAB software package. In t his paper, two three-story NN are created to input the extracted DNA character v ectors as samples into them. After the training, characters are extracted from t he 20 unclassified artificial sequence samples and 182 natural sequence samples to form the character vectors as input of the two NN for clustering. The result s shows: the clustering method presented in this paper can classify the DNA sequ ences in quite high accuracy and precision. It is quite feasible to apply the ar tificial neural network to DNA sequence clustering.更多还原