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Samira-VP: A simple protein alignment method with rechecking the alphabet vector positions

机译:Samira-VP:一种简单的蛋白质对准方法,重新检查字母矢量位置

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摘要

Protein structure alignment and comparisons that are based on an alphabetical demonstration of protein structure are more simple to run with faster evaluation processes; thus, their accuracy is not as reliable as three-dimension (3D)-based tools. As a 1D method candidate, TS-AMIR used the alphabetic demonstration of secondary-structure elements (SSE) of proteins and compared the assigned letters to each SSE using the n-gram method. Although the results were comparable to those obtained via geometrical methods, the SSE length and accuracy of adjacency between SSEs were not considered in the comparison process. Therefore, to obtain further information on accuracy of adjacency between SSE vectors, the new approach of assigning text to vectors was adopted according to the spherical coordinate system in the present study. Moreover, dynamic programming was applied in order to account for the length of SSE vectors. Five common datasets were selected for method evaluation. The first three datasets were small, but difficult to align, and the remaining two datasets were used to compare the capability of the proposed method with that of other methods on a large protein dataset. The results showed that the proposed method, as a text-based alignment approach, obtained results comparable to both 1D and 3D methods. It outperformed 1D methods in terms of accuracy and 3D methods in terms of runtime.
机译:蛋白质结构对准和基于蛋白质结构的字母展示的比较更易于使用更快的评估过程来运行;因此,它们的准确性不像三维(3D)的工具那样可靠。作为1D方法候选,TS-AMIR使用蛋白质的二级结构元素(SSE)的字母顺序演示,并使用N-GRAM方法将分配的字母与每个SSE进行比较。尽管结果与通过几何方法获得的结果相当,但在比较过程中不考虑SSE之间的SSE长度和SSE之间的邻接的准确性。因此,为了获得关于SSE矢量之间邻接的准确性的进一步信息,根据本研究中的球形坐标系采用了分配给载体的新方法。此外,应用了动态编程,以便考虑SSE矢量的长度。选择五个常用数据集进行方法评估。前三个数据集很小,但难以对齐,并且剩余的两个数据集用于比较所提出的方法在大蛋白质数据上的其他方法的能力。结果表明,作为基于文本的对准方法的提出方法,获得了与1D和3D方法相当的结果。在运行时,它在准确性和3D方法方面表现优于1D方法。

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