首页> 外文会议>33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society >Effects of windowing and zero-padding on Complex Resonant Recognition Model for protein sequence analysis
【24h】

Effects of windowing and zero-padding on Complex Resonant Recognition Model for protein sequence analysis

机译:加窗和零填充对蛋白质序列分析的复杂共振识别模型的影响

获取原文

摘要

Signal processing techniques such as Fourier Transform have widely been studied and successfully applied in many different areas. Techniques such as zero-padding and windowing have been developed and found very useful to improve the outcome of the signal processing methods. Resonant Recognition Model (RRM) and Complex Resonant Recognition Model (CRRM) that are based on the discrete Fourier Transform and widely used for the analysis of protein sequences do not consider such methods, which can however improve or alter the features extracted from the protein sequences. Therefore, in this paper, an extensive analysis was carried out to investigate into the influence of the zero-padding and windowing on the features extracted from the Complex Resonant Recognition Model. In order to present such effects, five different classes of influenza A virus Neuraminidase genes, which include H1N1, H1N2, H2N2, H3N2 and H5N1 genes, were used as a case study. For each of the Influenza A subtypes, two sets of Common Frequency Peaks (CFP) were extracted, one where windowing is applied and the other one where windowing is suppressed, for each signal length set for the analysis. In order to make all the signals (protein sequence) the same length, zero-padding was used. The signal lengths used in this study are set to 470, which is the maximum protein length, and also 512, 1024, 2048, 4096, 8192 and 16384 for further analysis. The results suggest that the windowing and zero-padding have key impact on CFP extracted from the Influenza A subtypes as the best match with CFP extracted from influenza A subtypes using CRRM is when the signal length of 4096 and windowing were both applied. Therefore, the outcome of this study should be taken into consideration for more accurate and reliable analysis of the protein sequences.
机译:诸如傅立叶变换之类的信号处理技术已被广泛研究并成功应用于许多不同领域。已经开发了诸如零填充和开窗的技术,并且发现它们对于改善信号处理方法的结果非常有用。基于离散傅里叶变换且广泛用于蛋白质序列分析的共振识别模型(RRM)和复杂共振识别模型(CRRM)不考虑此类方法,但是可以改善或更改从蛋白质序列中提取的特征。因此,本文进行了广泛的分析,以研究零填充和加窗对从复杂共振识别模型提取的特征的影响。为了表现出这样的效果,以H1N1,H1N2,H2N2,H3N2和H5N1基因为代表,研究了5种不同的甲型流感病毒神经氨酸酶基因。对于每种甲型流感病毒,为分析设置的每个信号长度,提取了两组通用频率峰值(CFP),一组使用加窗,而另一组使用加窗。为了使所有信号(蛋白质序列)具有相同的长度,使用了零填充。本研究中使用的信号长度设置为470(这是最大蛋白质长度),还设置为512、1024、2048、4096、8192和16384,以进行进一步分析。结果表明加窗和零填充对从A型流感亚型中提取的CFP与使用CRRM从A型流感亚型中提取的CFP的最佳匹配是在信号长度为4096和加窗的情况下。因此,对于蛋白质序列的更准确和可靠的分析,应考虑这项研究的结果。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号