关键词: 编码区识别, 信号处理, 随机森林, 深度置信网络（DBN）, 短时傅里叶变换（STFT）

Abstract:

To identify the protein coding regions in eukaryotic DNA sequences, a combination model based on Deep Belief Network（DBN） is proposed. Firstly, the DNA sequence of eukaryotes is converted numerically by signal processing technology and combined with statistical knowledge to extract the numerical features of the transformed DNA sequence. Secondly, the dimensionality of the extracted features variables is reduced by random forest. Then, the DNA sequence is classified and distinguished by deep belief network model. Finally, the Short Time Fourier Transform（STFT） is used to locate the external exons accurately. The results show that the accuracy and specificity of deep belief network combination model are better than those of Logistic regression model and Bayes discriminant model.

Key words: coding region identification, signal processing, random forest, Deep Belief Network（DBN）, Short Time Fourier Transform（STFT）