ISCAS OpenIR
基因识别及其算法研究
Alternative TitleNoise Suppression Based Algorithm for Gene Recognition
古毅伟; 王松; 张旭; 张茹; 刘建毅; 仝辉
2013
Source数学的实践与认识
ISSN1000-0984
Volume43Issue:14Pages:66-76
English Abstract针对基因识别问题,基于DNA序列的3周期这一性质,首先给出了DNA序列功率和信噪比的快速算法并讨论了不同物种基因类型的阈值确定方法;在此基础上,建立了基于背景噪声抑制和频谱平滑的SNR频谱预处理模型,经过预处理后的频谱不仅大幅度抑制了背景噪声,同时保留了SNR频谱的模式特征.在编码序列识别上,对经典的EPND预测算法进行了改进,使用改进的EPND算法对经过预处理后频谱进行基因识别,实验结果显示这种基因识别模型具有优异的基因识别性能,比传统直接使用基于滑动窗口DFT的EPND识别算法在敏感度、特异性等评价指标上提高了2%-2%左右.
Indexed TypeCSCD
AbstractTo solve the problem of gene recognition, this paper presents a fast algorithm to compute the power and SNR for given DNA sequences and discusses the determination method for threshold of different species gene type; On the basis, this paper proposes an SNR sequence preprocessing model based on background noise suppression and spectrum smoothing. After such a preprocessing, the SNR spectrum remains its pattern characteristics with the background noise suppressed. On the recognition of coded sequence, this paper improves the classical EPND predication algorithm which works on the preprocessed gene SNR sequence. The experiment shows the new improved algorithm gains an excellent performance, which improves 2%-12% on major evaluation indexes compared to conventional method based on sliding window DFT and EPND recognition algorithm.
Keyword基因识射 频谱分析 噪声抑制 Epnd 滤波 信噪比 Gene Recognition Spectrum Analysis Noise Suppression Epnd Filtering Snr
Department北京邮电大学计算学院,北京,100876 中国科学院软件研究所,北京,100190 北京邮电大学信息与通信工程学院,北京,100876 北京邮电大学理学院,北京,100876
Language中文
CSCD IDCSCD:4971442
Content Type期刊论文
URIhttp://ir.iscas.ac.cn/handle/311060/16801
Collection中国科学院软件研究所
Recommended Citation
GB/T 7714
古毅伟,王松,张旭,等. 基因识别及其算法研究[J]. 数学的实践与认识,2013,43(14):66-76.
APA 古毅伟,王松,张旭,张茹,刘建毅,&仝辉.(2013).基因识别及其算法研究.数学的实践与认识,43(14),66-76.
MLA 古毅伟,et al."基因识别及其算法研究".数学的实践与认识 43.14(2013):66-76.
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