Chrysostomou Charalambos, Seker Huseyin, Aydin Nizamettin
Department of Genetics, University of Leicester, University Road, Leicester LE1 7RH, UK.
Department of Computer Science and Digital Technologies, Faculty of Engineering and Environment, The University of Northumbria at Newcastle, Newcastle-upon-Tyne NE1 8ST, UK.
Adv Bioinformatics. 2015;2015:909765. doi: 10.1155/2015/909765. Epub 2015 Jan 6.
Complex informational spectrum analysis for protein sequences (CISAPS) and its web-based server are developed and presented. As recent studies show, only the use of the absolute spectrum in the analysis of protein sequences using the informational spectrum analysis is proven to be insufficient. Therefore, CISAPS is developed to consider and provide results in three forms including absolute, real, and imaginary spectrum. Biologically related features to the analysis of influenza A subtypes as presented as a case study in this study can also appear individually either in the real or imaginary spectrum. As the results presented, protein classes can present similarities or differences according to the features extracted from CISAPS web server. These associations are probable to be related with the protein feature that the specific amino acid index represents. In addition, various technical issues such as zero-padding and windowing that may affect the analysis are also addressed. CISAPS uses an expanded list of 611 unique amino acid indices where each one represents a different property to perform the analysis. This web-based server enables researchers with little knowledge of signal processing methods to apply and include complex informational spectrum analysis to their work.
开发并展示了用于蛋白质序列的复杂信息谱分析(CISAPS)及其基于网络的服务器。正如最近的研究表明,在使用信息谱分析蛋白质序列时,仅使用绝对谱被证明是不够的。因此,开发CISAPS是为了考虑并提供三种形式的结果,包括绝对谱、实谱和虚谱。在本研究中作为案例研究呈现的与甲型流感亚型分析相关的生物学特征,也可能单独出现在实谱或虚谱中。正如所呈现的结果,蛋白质类别可能根据从CISAPS网络服务器提取的特征呈现相似性或差异。这些关联可能与特定氨基酸指数所代表的蛋白质特征有关。此外,还解决了各种可能影响分析的技术问题,如零填充和加窗。CISAPS使用了一个包含611个独特氨基酸指数的扩展列表,其中每个指数代表不同的属性来进行分析。这个基于网络的服务器使对信号处理方法了解甚少的研究人员能够在其工作中应用并纳入复杂信息谱分析。